Energy consumption optimization method and system for integrating building structure parameters

Abstract

The invention discloses an energy consumption optimization method for integrating building structure parameters. The method comprises the following steps: acquiring geometric morphology, enclosure structure, equipment configuration, personnel activity and external environment data of a building in real time by using an intelligent sensor and a building information model; based on the collected data, calculating thermal load and energy consumption distribution of the building, extracting energy efficiency performance indexes, and establishing an energy efficiency baseline model; the thermal performance of the building envelope structure is dynamically adjusted by utilizing a self-adaptive envelope structure technology so as to adapt to external climate change and internal thermal load requirements; based on the optimized enclosure structure characteristics, an energy recovery system is started, and waste heat and air flow energy in the building are converted into available energy; in combination with energy efficiency data fed back in real time, the intelligent scheduling system dynamically adjusts the operation strategy of the building equipment, optimizes the energy efficiency, reduces unnecessary energy consumption and improves the comfort level; the building energy efficiency is evaluated regularly, and it is ensured that the building continuously maintains the optimal energy efficiency under different seasons, environment changes and use requirements.

Description

Technical Field

[0001] This invention relates to the field of building energy efficiency optimization technology, specifically to an energy consumption optimization method and system that integrates building structural parameters. Background Technology

[0002] With increasing global energy consumption and growing environmental awareness, building energy efficiency optimization has become a key area in building design and management. Buildings consume significant amounts of energy during their use, particularly during the operation of heating, ventilation, and air conditioning (HVAC) systems, lighting systems, and other electrical equipment. Furthermore, the thermal performance of the building facade and envelope also significantly impacts building energy efficiency. Traditional building envelopes often lack flexibility and cannot adequately cope with changes in the external environment and fluctuations in internal heat load.

[0003] Existing building energy efficiency optimization methods mostly focus on reducing energy consumption by increasing insulation materials or improving equipment efficiency. However, these methods typically rely on fixed designs and parameters, making it impossible to dynamically adjust them according to environmental changes and actual building usage. With the rise of smart building technologies, optimizing building energy efficiency through real-time data monitoring and intelligent control has become a trend, but some technical challenges remain.

[0004] Currently, most building energy efficiency optimization technologies fail to effectively integrate multiple aspects such as building design, building envelope, energy recovery, and equipment scheduling, and their flexibility and real-time adjustment capabilities in response to complex environmental changes remain insufficient. Furthermore, despite existing research and applications of energy recovery systems and adaptive materials, how to efficiently combine these technologies to achieve comprehensive building energy efficiency optimization remains an unsolved technical challenge.

[0005] Therefore, how to optimize building energy efficiency through integrated technical solutions based on factors such as building structural parameters, building envelope, energy recovery system, and intelligent scheduling has become an important topic in current building energy efficiency research and application. Summary of the Invention

[0006] This invention provides an energy consumption optimization method integrating building structural parameters, comprising: S10. Through intelligent sensors and building information modeling systems, collect data on the building's geometry, envelope, equipment configuration, human activities, and external environment in real time. S20. Based on the collected data, use building energy efficiency analysis tools to calculate the building's heat load and energy consumption distribution, extract building energy efficiency performance indicators, and establish a building energy efficiency baseline model. S30. Based on the energy efficiency baseline model, adaptive building envelope technology is used to dynamically adjust the thermal performance of the building envelope to adapt to external climate change and internal heat load demand. S40. Based on the optimized building envelope characteristics, activate the energy recovery system to utilize the waste heat and airflow energy generated inside the building and convert them into usable energy for the building system. S50 combines real-time feedback of energy efficiency data and building equipment status to intelligently schedule building equipment operation strategies in order to optimize building energy efficiency, reduce unnecessary energy consumption, and improve comfort. S60. Based on the adjusted equipment operation strategy and real-time energy efficiency monitoring data, regularly assess and adjust the building's energy efficiency to ensure that the building maintains optimal energy efficiency under different seasons, environmental changes and usage needs.

[0007] The energy consumption optimization method integrating building structural parameters as described above involves real-time data collection of building geometry, envelope, equipment configuration, human activity, and external environment data through intelligent sensors and a building information modeling system, including: S101. By deploying smart sensors inside the building, environmental data such as temperature, humidity, CO2 concentration, human activity, and power load inside and outside the building are collected. S102. Obtain structural data such as the building's geometry, envelope materials, and equipment configuration through a building information modeling system, and integrate and analyze this data with data collected by sensors.

[0008] The energy consumption optimization method integrating building structural parameters as described above includes, based on collected data, using building energy efficiency analysis tools to calculate the building's heat load and energy consumption distribution, extracting building energy efficiency performance indicators, and establishing a building energy efficiency baseline model, including: S201. Calculate the internal and external heat loads of a building using building energy efficiency simulation tools, taking into account the heat conduction characteristics of the building envelope and the loads of equipment and personnel activities within the building. S202. Based on the heat load calculation results, extract the building's energy efficiency performance indicators and establish a building energy efficiency baseline model based on these indicators.

[0009] An energy consumption optimization method integrating building structural parameters as described above, wherein, based on an energy efficiency baseline model, adaptive building envelope technology is used to dynamically adjust the thermal performance of the building envelope to adapt to external climate change and internal heat load demands, including: S301. Evaluate the thermal performance of building envelopes such as facades, windows, and walls based on the energy efficiency baseline model, and adjust the design of the building envelope according to external climate conditions and building load requirements. S302. Utilize adaptive materials to dynamically adjust the thermal conductivity of the building envelope, enabling the building to optimize its heat load under different seasons and environmental conditions.

[0010] The energy consumption optimization method for integrated building structural parameters described above includes, based on the optimized building envelope characteristics, activating an energy recovery system to convert waste heat and airflow energy generated within the building into usable energy for the building system, comprising: S401. Based on the optimized thermal performance of the building envelope, calculate the waste heat generated inside the building and activate the heat recovery system to recover the waste heat. S402. Activate the airflow energy recovery device to convert the airflow energy generated by air conditioning, ventilation systems, etc., into heat or electricity to supplement the building's energy needs.

[0011] The energy consumption optimization method integrating building structural parameters as described above, wherein, by combining real-time feedback energy efficiency data and building equipment status, intelligent scheduling of building equipment operation strategies is implemented to optimize building energy efficiency, reduce unnecessary energy consumption, and improve comfort, including: S501. Monitor the operating status of building equipment in real time through the intelligent scheduling system, and adjust the operating parameters of the equipment according to the external environment and indoor needs; S502. Based on data such as temperature and humidity and human activity within the building, dynamically adjust the operating status of building equipment to optimize energy use and improve comfort.

[0012] The energy consumption optimization method integrating building structural parameters as described above, wherein, based on adjusted equipment operation strategies and real-time energy efficiency monitoring data, building energy efficiency is periodically evaluated and adjusted to ensure that the building continuously maintains optimal energy efficiency under different seasons, environmental changes, and usage demands, including: S601. By combining real-time feedback energy efficiency monitoring data and the operating status of building equipment, the energy efficiency of the building is regularly assessed to identify areas for optimization. S602. Adjust the operating parameters and system configuration of building equipment according to the energy efficiency assessment results to ensure that the building maintains optimal energy efficiency during long-term operation.

[0013] This invention also provides an energy consumption optimization system integrating building structural parameters, comprising: The data acquisition module is used to collect data on the building's geometry, envelope, equipment configuration, personnel activities, and external environment in real time through an intelligent sensor network and a building information modeling system. The energy efficiency analysis module is used to calculate the building's heat load and energy consumption distribution based on the collected data, using building energy efficiency analysis tools, and to extract building energy efficiency performance indicators and establish a building energy efficiency baseline model. The adaptive building envelope adjustment module is used to dynamically adjust the thermal performance of the building envelope based on the energy efficiency baseline model to adapt to external climate change and internal heat load demand. The energy recovery module is used to activate the energy recovery system based on the optimized building envelope characteristics, and to convert the waste heat and airflow energy generated inside the building into usable energy for the building system. The equipment scheduling module is used to combine real-time feedback energy efficiency data and building equipment status to intelligently schedule the operation strategy of building equipment in order to optimize building energy efficiency, reduce unnecessary energy consumption, and improve comfort. The energy efficiency assessment module is used to periodically assess and adjust building energy efficiency based on adjusted equipment operation strategies and real-time energy efficiency monitoring data, ensuring that buildings maintain optimal energy efficiency under different seasons, environmental changes, and usage demands.

[0014] The beneficial effects achieved by this invention are as follows: By integrating building structural parameters with real-time environmental data, an energy efficiency baseline model is established and combined with adaptive building envelope adjustment, energy recovery system and intelligent equipment scheduling, dynamic optimization of building energy efficiency is realized; not only is energy consumption effectively reduced, but indoor comfort is also improved, and continuous monitoring and periodic evaluation ensure that the building maintains efficient and stable operation in the long term under different environmental conditions and usage requirements. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is a flowchart of an energy consumption optimization method integrating building structural parameters provided in Embodiment 1 of this application; Figure 2 This is a schematic diagram of an energy consumption optimization system integrating building structural parameters provided in Embodiment 2 of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 like Figure 1 As shown, Embodiment 1 of this application provides an energy consumption optimization method integrating building structural parameters, comprising the following steps: S10. Through intelligent sensors and building information modeling systems, real-time data on building geometry, envelope, equipment configuration, human activity, and external environment are collected.

[0019] Specifically, various types of intelligent sensors are deployed within the building space to collect environmental parameters and energy consumption data in real time, while simultaneously calling upon the Building Information Modeling (BIM) system to output static structural information of the building. The dynamic operational data collected by the sensors is combined with the geometric and material data from the BIM system to form a multi-dimensional data set reflecting the building's structure and operational status. This set encompasses both the building's physical geometric characteristics and real-time energy consumption and occupant usage characteristics. The specific steps include the following: S101. By deploying smart sensors inside the building, environmental data such as temperature, humidity, CO2 concentration, human activity, and power load inside and outside the building are collected. Specifically, temperature and humidity sensors, air quality monitors, and infrared human body sensors are installed on different floors, in main rooms, and at external environmental nodes to acquire spatial thermal and humidity conditions, carbon dioxide concentration levels, and the frequency of human activity, respectively. Power monitoring modules are installed in building lighting circuits, air conditioning systems, and main power distribution branches to record the voltage, current, and instantaneous power of various energy-consuming devices. These sensors are connected to a central data acquisition controller via wireless communication or a wired bus, with all data being collected synchronously at a frequency of at least 1 Hz. The collected operational data is filtered, outlier removed, and timestamp-calibrated to form a time-consistent, spatially complete environmental and energy consumption dataset, comprehensively reflecting the dynamic operational characteristics of the building under different environmental conditions and occupancy states.

[0020] S102. Obtain structural data such as the building's geometry, envelope materials, and equipment configuration through a building information modeling system, and integrate and analyze this data with data collected by sensors.

[0021] Specifically, the BIM system includes a three-dimensional geometric model of the building, covering information such as floor area, floor height, envelope layout, and equipment installation locations. It also records the physical properties of enclosure components such as walls, roofs, doors, and windows (e.g., heat transfer coefficient, insulation thickness, and light transmittance) and configuration parameters of electromechanical equipment (e.g., rated power of air conditioning units, lighting system installation density, and power distribution system circuit distribution). In this step, the aforementioned static parameters are first exported from the BIM database, and then spatial mapping and parameter alignment are performed with dynamic data collected by sensors using a data fusion algorithm. For example, temperature and humidity sensor data located in the east-facing room are bound to the corresponding geometric unit of the room in the BIM model; data collected by the power monitoring module is associated with the corresponding electrical circuit object in the BIM. Through a unified data interface and time synchronization mechanism, a comprehensive database covering "building geometry—material properties—equipment configuration—operating environment" is established. This database can dynamically update operational data while ensuring the integrity of static parameters, providing accurate and sustainable input support for the construction of the energy efficiency baseline model.

[0022] S20. Based on the collected data, use building energy efficiency analysis tools to calculate the building's heat load and energy consumption distribution, extract building energy efficiency performance indicators, and establish a building energy efficiency baseline model.

[0023] This step aims to perform in-depth analysis of the collected data to calculate the building's heat load and energy consumption distribution, and extract energy efficiency performance indicators. These calculation results enable an accurate assessment of the building's energy efficiency performance and the establishment of an energy efficiency baseline model. Specifically, it includes the following sub-steps: S201. Calculate the internal and external heat loads of a building using building energy efficiency simulation tools, taking into account the heat conduction characteristics of the building envelope and the loads of equipment and personnel activities within the building. First, the heat load of the building envelope is calculated. The heat load calculation of the envelope mainly considers its heat conduction characteristics and the temperature difference between it and the external environment. Therefore, a building energy efficiency simulation tool is used to conduct a detailed analysis of each component of the building envelope. Specifically, for each component (such as exterior walls, windows, roof, etc.), its heat conduction load is calculated using the following formula: ,in, Let be the heat load of the i-th building envelope, representing the heat generated by the building envelope due to changes in the external environment; n is the total number of building envelopes. Let be the thermal conductivity coefficient of the i-th building envelope, whose value represents the thermal conductivity of the material; The area of ​​the building envelope, i.e., the surface area of ​​the building facade, roof, or windows; and These are the temperature differences between the inside and outside of the building, i.e., the driving force for heat transfer between the inside and outside of the building; Here, is the temperature correction function for the material, which describes the adjustment of the material's thermal conductivity as temperature changes. It is the current temperature of the material; It is the reference temperature of the material. It is the initial thermal conductivity coefficient of the material. This is the temperature dependence coefficient of the material's thermal conductivity, where n is the exponential term, adjusting for the magnitude of the effect of temperature on thermal conductivity. Based on this formula, the heat load of each building envelope can be calculated, and thus the overall heat load of the building can be determined.

[0024] Besides the building envelope, internal equipment (such as air conditioning, lighting systems, and appliances) and occupant activities also affect the building's heat load. Therefore, the load from internal heat sources also needs to be considered, which is calculated using the following formula: ,in, The heat load generated by equipment and personnel activities inside the building; m is the number of heat sources inside the building. Let j be the power of the j-th device or heat source; This is a time-varying heat load factor, representing the heat load from personnel activities and equipment use. The total heat load of a building is obtained by calculating the heat loads of the building envelope and internal equipment. This provides input data for subsequent energy efficiency analysis.

[0025] S202. Based on the heat load calculation results, extract the building's energy efficiency performance indicators and establish a building energy efficiency baseline model based on these indicators.

[0026] Based on the building heat load data calculated using S201, the building's energy efficiency performance indicators are extracted. The Energy Efficiency Ratio (EER) is one of the core indicators for evaluating building energy efficiency, and its specific calculation method is as follows: ,in, It is the theoretical energy consumption of a building under ideal environmental conditions; It refers to the energy consumption of a building during actual operation. By calculating EER, the building's energy efficiency is quantified, and the gap between the building's current operating state and its ideal state is assessed.

[0027] Besides Energy Efficiency Ratio (EER), another important energy efficiency indicator is Energy Intensity (EUI), which reflects the energy consumption per unit area of ​​a building. The calculation formula is as follows: ,in, It is the building’s actual annual energy consumption, including the total energy consumption of all external and internal loads; It represents the building's total floor area. The lower the EUI value, the better the building's energy efficiency per unit area, and the greater the potential for energy efficiency optimization.

[0028] Considering the fluctuations in building energy efficiency and combining the dynamic changes in building energy efficiency under different environmental conditions, a dynamic energy efficiency correction model is proposed. The specific formula is as follows: ,in, It is a revised energy efficiency performance index that takes into account the impact of temperature changes on building energy efficiency; It is the building's actual annual energy consumption; It is the temperature difference between the inside and outside of the building; It is a correction factor, representing the sensitivity of energy efficiency to temperature changes; This refers to the total floor area of ​​the building. This formula can be used to account for the direct impact of temperature fluctuations on building energy efficiency, especially in cases of seasonal changes, outdoor climate changes, and large temperature differences between the building's interior and exterior environments. Through energy efficiency correction models, the building's energy efficiency level can be quantified more accurately.

[0029] Based on the aforementioned energy efficiency indicators, a baseline energy efficiency model for buildings can be further established. This model details the building's energy efficiency performance under different environmental conditions and usage states. By comparing this model with historical energy efficiency data, dynamic monitoring and adjustment of energy efficiency can be achieved.

[0030] S30. Based on the energy efficiency baseline model, adaptive building envelope technology is used to dynamically adjust the thermal performance of the building envelope to adapt to external climate change and internal heat load demand.

[0031] In this step, the building envelope (such as exterior walls, roof, and windows) is dynamically adjusted using the aforementioned energy efficiency baseline model as a reference. By introducing adaptive materials with variable thermal conductivity and light transmittance, and combining real-time external climate parameters and internal heat load requirements, the building envelope is adjusted to optimize overall building energy efficiency. Specifically, this includes the following sub-steps: S301. Evaluate the thermal performance of building envelopes such as facades, windows, and walls based on the energy efficiency baseline model, and adjust the design of the building envelope according to external climate conditions and building load requirements. First, the thermal conductivity characteristics of the building envelope are evaluated using a baseline model. The heat transfer of the building envelope is related to the structural area, thermal conductivity, and the temperature difference between the inside and outside. Its instantaneous heat flux can be expressed as: ,in, Let be the heat transfer of the i-th enclosure component; The heat transfer coefficient; For the enclosure area; and These are the outdoor and indoor temperatures, respectively.

[0032] To introduce the feasibility of adaptive adjustment, a temperature difference correction function is defined to adjust the heat transfer coefficient: ,in, This is the adjustment amplitude factor; This is influenced by periodic factors of the external climate (such as diurnal temperature fluctuations). Therefore, the equivalent heat transfer coefficient of the building envelope can dynamically change with environmental fluctuations.

[0033] This assessment allows for the determination of the optimal design parameter range for the building envelope under current conditions, based on real-time external climate (temperature, humidity, solar radiation, etc.) and internal load requirements (personnel density, equipment operation status).

[0034] S302. Utilize adaptive materials to dynamically adjust the thermal conductivity of the building envelope, enabling the building to optimize its heat load under different seasons and environmental conditions.

[0035] In this sub-step, phase change materials or thermochromic materials with adjustable thermal properties are used to adjust the thermal conductivity of the building envelope in real time. Phase change materials can absorb or release heat when the temperature is close to the phase change point, and their equivalent thermal conductivity can be defined as: ,in, Let T be the thermal conductivity at temperature T. Based on thermal conductivity; This is the adjustment coefficient; The phase transition temperature; To control the phase transition bandwidth, this function reflects the characteristic of increased thermal conductivity as the temperature approaches the phase transition point, thereby enhancing the building's ability to absorb and release heat.

[0036] At the overall level, the building's total heat load can be written as: This expression will adaptively adjust the heat transfer coefficient. This is incorporated into the calculations, thus reflecting the real-time thermal characteristics of the building envelope. Through the analysis of... Continuous optimization enables buildings to achieve heat insulation in summer and heat preservation in winter, thereby reducing the load on air conditioning and heating.

[0037] S40. Based on the optimized building envelope characteristics, activate the energy recovery system to convert waste heat and airflow energy generated inside the building into usable energy for the building system.

[0038] In this step, the energy recovery system is activated using the performance of the building envelope adjusted by S30. Energy losses caused by the operation of internal equipment, occupant activities, and airflow are recovered and converted into heat or electricity, achieving energy reuse in the building. Specifically, this includes the following sub-steps: S401. Based on the optimized thermal performance of the building envelope, calculate the waste heat generated inside the building and activate the heat recovery system to recover the waste heat. First, based on the optimized building envelope characteristics, the waste heat generated by internal equipment, occupant activities, and lighting is assessed. Waste heat is not only related to equipment power but also affected by the heat transfer characteristics of the building envelope. Therefore, the following calculation method is proposed: ,in, t represents the total waste heat of the building at time t; m represents the number of internal equipment and active heat sources; n represents the number of building envelope zones. Let J be the rated power of the j-th device; Let be the waste heat efficiency factor of the j-th device, which varies with the operating status of the device; Let be the dynamic heat transfer coefficient of the i-th building envelope; The area of ​​the enclosure structure; This is a correction factor for building envelope heat recovery. This formula combines waste heat generated inside the building with heat losses in the building envelope, resulting in a more realistic waste heat distribution. The heat recovery system uses heat exchange devices to recover and store this waste heat for use in the building's air conditioning or hot water systems.

[0039] S402. Activate the airflow energy recovery device to convert the airflow energy generated by air conditioning, ventilation systems, etc., into heat or electricity to supplement the building's energy needs.

[0040] During the daily operation of a building, the airflow generated by equipment such as air conditioning and ventilation systems carries a significant amount of energy. Through appropriate recovery devices, buildings can convert this airflow energy into heat or electricity to supplement their energy needs, thereby reducing dependence on external energy sources and improving the building's energy self-sufficiency.

[0041] The core of airflow energy recovery is capturing and converting the kinetic energy in airflow. Typically, air conditioning and ventilation systems within buildings generate relatively high airflow velocities, and the kinetic energy in the air can be effectively recovered through devices such as wind turbines and air heat exchangers. To quantify this process, the following formula is proposed: ,in, The total energy recovered by the building through airflow within time t; The number of airflow sources refers to the various airflow channels in the air conditioning and ventilation systems within a building. Let be the air density of the k-th flow source; Let be the air velocity of the k-th flow source; Let be the cross-sectional area of ​​the k-th flow source; Airflow energy recovery efficiency (AFE) indicates the efficiency with which a recovery device can effectively convert airflow energy. By recovering energy carried by airflow, buildings can effectively reduce their demand for external energy and improve energy efficiency. The recovered energy can be used to assist the building's air conditioning system or to meet internal energy needs such as providing hot water.

[0042] The S50 combines real-time feedback of energy efficiency data and building equipment status to intelligently schedule building equipment operation strategies, thereby optimizing building energy efficiency, reducing unnecessary energy consumption, and improving comfort.

[0043] This step utilizes an intelligent scheduling system, combining real-time feedback of energy efficiency data with the operating status of building equipment, to schedule the operating modes of building equipment, thereby maximizing building energy efficiency, reducing unnecessary energy consumption, and improving indoor comfort. The system automatically adjusts equipment operating parameters based on changes in the external environment and indoor needs (such as temperature, humidity, and occupant activity) to ensure an optimal balance between building energy efficiency and comfort. Specifically, it includes the following sub-steps: S501. Monitor the operating status of building equipment in real time through the intelligent scheduling system, and adjust the operating parameters of the equipment according to the external environment and indoor needs; The intelligent dispatching system monitors the operating status of building equipment in real time and dynamically adjusts it based on external environmental data (such as temperature, humidity, and climate) and indoor demand data (such as temperature, humidity, and human activity). The system automatically adjusts the operating load of air conditioning according to changes in outdoor temperature, or automatically adjusts the brightness of lighting equipment according to changes in human activity, thereby achieving efficient energy use.

[0044] Specifically, the intelligent scheduling system will calculate the adjustment intensity of the equipment based on real-time data. This determines the power adjustment amount for each device. The formula for calculating the adjustment intensity is as follows: ,in, Let be the change in the regulating power of device k at time t; and These are the maximum and minimum power values ​​of device k, respectively; This is the difference between the indoor temperature and the set temperature. Indoor heat load is generated by human activities, lighting, equipment, etc. External climatic conditions, such as outdoor temperature and humidity; , where is the weighting coefficient, representing the sensitivity of each factor to the equipment. This formula calculates the equipment's adjustment intensity based on changes in indoor and outdoor temperature difference, heat load, and external climate, thereby maximizing energy efficiency while ensuring a comfortable environment.

[0045] S502. Based on data such as temperature and humidity and human activity within the building, dynamically adjust the operating status of building equipment to optimize energy use and improve comfort.

[0046] The intelligent scheduling system further dynamically adjusts the operating status of building equipment based on real-time data such as temperature, humidity, and personnel activity. By analyzing the collected data, the system adjusts the load of equipment such as air conditioning, lighting, and heating to optimize energy use and improve comfort. When personnel activity increases, the system automatically increases the power of air conditioning or lighting systems to ensure a comfortable environment; while when personnel activity is low, the system reduces the workload of equipment to avoid unnecessary energy consumption.

[0047] To further optimize equipment operation, an equipment operation optimization coefficient is set. The operating efficiency of the equipment is expressed by the following formula: ,in, The optimal operating coefficients for device k at time t; and These represent the actual power consumption and ideal power consumption of device k at time t, respectively. and The environmental sensitivity coefficient reflects the equipment's ability to respond to changes in indoor temperature differences and the external environment. This represents the current indoor heat load. This represents the building's maximum heat load. The optimization coefficient dynamically adjusts the equipment's operating intensity based on the ratio of actual power consumption to ideal power consumption, taking into account changes in environmental factors, to achieve maximum energy efficiency. This helps the system determine whether the equipment needs to adjust its operating intensity or cease operation, thereby maximizing energy efficiency.

[0048] S60. Based on the adjusted equipment operation strategy and real-time energy efficiency monitoring data, regularly assess and adjust the building's energy efficiency to ensure that the building maintains optimal energy efficiency under different seasons, environmental changes and usage needs.

[0049] This step involves regularly assessing the building's energy efficiency performance, combined with real-time feedback on energy efficiency monitoring data and equipment operating status, to ensure that the building can consistently maintain optimal energy efficiency under different seasons, environmental changes, and usage demands. By dynamically adjusting equipment operating parameters and system configuration, the system can maximize the building's energy use and reduce unnecessary energy consumption while ensuring comfort. Specifically, it includes the following sub-steps: S601. By combining real-time feedback energy efficiency monitoring data and the operating status of building equipment, the energy efficiency of the building is regularly assessed to identify areas for optimization. In this step, the intelligent scheduling system periodically assesses the building's energy efficiency level. Based on real-time energy efficiency monitoring data, the system analyzes the building's current energy efficiency performance and compares it with ideal values ​​or historical data. In this way, the system can identify inefficient aspects of building operation and provide a basis for subsequent optimization. When the energy efficiency assessment result is lower than the set standard, the system marks it as an optimization target, helping to identify areas for improvement and providing data support for subsequent adjustments.

[0050] S602. Adjust the operating parameters and system configuration of building equipment according to the energy efficiency assessment results to ensure that the building maintains optimal energy efficiency during long-term operation.

[0051] Based on energy efficiency assessment results, the intelligent dispatch system will adjust the operating parameters and configurations of building equipment to ensure continuous optimization of building energy efficiency. Adjustments include equipment power regulation, operating mode optimization, and system configuration updates. Specific adjustment measures include: Equipment power regulation: Based on energy efficiency assessments, the system adjusts the power output of equipment such as air conditioners, lighting, and heating systems. The system can automatically adjust equipment power according to environmental needs, avoiding unnecessary energy waste.

[0052] Operation mode optimization: Adjust the operation modes of the air conditioning, ventilation, and lighting systems according to seasonal changes or usage needs. For example, the cooling mode of the air conditioning system may need to be enhanced in summer, while it may be optimized for heating mode in winter.

[0053] System configuration updates: During long-term operation, the system checks device configurations to ensure they adapt to changing environments and requirements. If equipment becomes outdated or technology advances, the system recommends upgrading or reconfiguring the equipment.

[0054] Example 2 like Figure 2 As shown, Embodiment 2 of this application provides an energy consumption optimization system integrating building structural parameters, comprising: The data acquisition module 21, through an intelligent sensor network and a Building Information Modeling (BIM) system, collects real-time data on the building's geometry, envelope, equipment configuration, human activity, and external environment. This module is responsible for installing and maintaining sensor equipment, collecting dynamic information such as temperature and humidity, CO2 concentration, human activity, and energy consumption data. Simultaneously, it calls upon the BIM system to output the building's static structural information, forming a comprehensive multi-dimensional dataset. Specifically, it includes the following sub-modules: The environmental data acquisition submodule 211 collects environmental data inside and outside the building in real time through devices such as temperature and humidity sensors, CO2 concentration monitors, and infrared human body sensors. This submodule is responsible for synchronous data acquisition and transmitting the data to the central data acquisition and control system via wireless or wired means.

[0055] The energy consumption data acquisition submodule 212, installed on power monitoring modules in equipment such as air conditioners, lighting, and power distribution systems, collects energy consumption data in real time, including information such as voltage, current, and instantaneous power. This data helps the system evaluate the operating status and energy efficiency of the equipment.

[0056] The energy efficiency analysis module 22 calculates the building's heat load and energy consumption distribution based on collected data using building energy efficiency analysis tools, extracts the building's energy efficiency performance indicators, and establishes a building energy efficiency baseline model. This module dynamically calculates the building's energy efficiency performance based on factors such as the building envelope's thermal conductivity, equipment operation, and human activity. Specifically, it includes the following sub-modules: The heat load calculation submodule 221 calculates the building's internal heat load based on factors such as the building envelope, equipment load, and occupant activity. This submodule uses building energy efficiency simulation tools to perform detailed analysis of the building's internal and external heat loads, providing real-time energy efficiency data.

[0057] The energy efficiency performance index extraction submodule 222 extracts energy efficiency indicators such as the building's energy efficiency ratio (EER) and energy use intensity (EUI) based on heat load and energy consumption data. These indicators enable the system to assess the building's energy efficiency level and provide data support for subsequent optimization.

[0058] The adaptive building envelope adjustment module 23, based on an energy efficiency baseline model, dynamically adjusts the thermal performance of the building envelope to adapt to external climate changes and internal heat load demands. This module optimizes the overall building energy efficiency by adjusting parameters such as the heat transfer coefficient and light transmittance of the building envelope in real time. Specifically, it includes the following sub-modules: The thermal performance evaluation submodule 231 of the building envelope uses an energy efficiency baseline model to evaluate the thermal performance of the building envelope, such as the facade, windows, and walls, and to determine the optimal heat transfer characteristics under the current environment.

[0059] The adaptive material adjustment submodule 232 introduces phase change materials or thermochromic materials to automatically adjust the thermal conductivity of the building envelope through temperature changes, thereby achieving the effects of heat insulation in summer and heat preservation in winter, and optimizing the building's heat load.

[0060] Energy recovery module 24, based on the optimized building envelope characteristics, activates the energy recovery system to convert waste heat generated inside the building and airflow energy into usable energy for the building system. This module recovers waste heat generated by airflow and equipment operation through heat exchangers and wind turbines. Specifically, it includes the following sub-modules: Waste heat recovery submodule 241 calculates the waste heat generated by equipment and personnel activities inside the building based on the thermal performance of the building envelope, and starts the heat recovery system to collect and store the waste heat for use in air conditioning or hot water systems.

[0061] The airflow energy recovery submodule 242 converts the airflow energy generated by the air conditioning and ventilation system into heat or electricity through devices such as wind turbines and air heat exchangers, thereby reducing external energy consumption.

[0062] The equipment scheduling module 25 combines real-time feedback energy efficiency data and building equipment status to intelligently schedule building equipment operation strategies, optimizing building energy efficiency, reducing unnecessary energy consumption, and improving comfort. This module dynamically adjusts equipment operating parameters based on the external environment and indoor needs to ensure a balance between comfort and energy efficiency. Specifically, it includes the following sub-modules: Equipment operation status monitoring submodule 251 monitors the operation status of various equipment (such as air conditioning, lighting, ventilation, etc.) in the building in real time, and dynamically adjusts the operation intensity of the equipment based on data such as temperature and humidity and personnel activities.

[0063] The energy efficiency regulation and scheduling strategy submodule 252 optimizes the working mode and operating intensity of building equipment based on real-time energy efficiency data, reducing energy waste and ensuring building comfort. This submodule calculates the regulation intensity of each device using formulas and models, dynamically adjusting the equipment load.

[0064] Energy Efficiency Assessment Module 26: Based on adjusted equipment operation strategies and real-time energy efficiency monitoring data, this module periodically assesses and adjusts building energy efficiency. Through regular assessments of energy efficiency indicators, this module helps identify deficiencies in building energy efficiency and makes adjustments to ensure that buildings maintain optimal energy efficiency under different seasons, environmental changes, and usage demands. Specifically, it includes the following sub-modules: The energy efficiency assessment submodule 261 calculates the building's energy efficiency performance based on the difference between the actual and ideal energy consumption of the equipment. This submodule assesses the fluctuations in building energy efficiency under different time periods and conditions, and identifies areas for optimization.

[0065] The energy efficiency adjustment and optimization submodule 262 adjusts the operating parameters, configuration, and system operation mode of the equipment based on the energy efficiency assessment results to ensure that the building always operates at the best energy efficiency.

[0066] Corresponding to the above embodiments, the present invention provides a computer storage medium, including: at least one memory and at least one processor; The memory is used to store one or more program instructions; A processor is used to run one or more program instructions to execute an energy consumption optimization method that integrates building structural parameters.

[0067] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide an energy consumption optimization method integrating building structural parameters.

[0068] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions that, when executed on a computer, cause the computer to perform the aforementioned energy consumption optimization method for integrated building structural parameters.

[0069] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0070] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0071] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0072] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0073] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0074] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0075] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0076] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing energy consumption by integrating building structural parameters, characterized in that, Includes the following steps: S10. Through intelligent sensors and building information modeling systems, collect data on the building's geometry, envelope, equipment configuration, human activities, and external environment in real time. S20. Based on the collected data, use building energy efficiency analysis tools to calculate the building's heat load and energy consumption distribution, extract building energy efficiency performance indicators, and establish a building energy efficiency baseline model. S30. Based on the energy efficiency baseline model, adaptive building envelope technology is used to dynamically adjust the thermal performance of the building envelope to adapt to external climate change and internal heat load demand. S40. Based on the optimized building envelope characteristics, activate the energy recovery system to utilize the waste heat and airflow energy generated inside the building and convert them into usable energy for the building system. S50 combines real-time feedback of energy efficiency data and building equipment status to intelligently schedule building equipment operation strategies in order to optimize building energy efficiency, reduce unnecessary energy consumption, and improve comfort. S60. Based on the adjusted equipment operation strategy and real-time energy efficiency monitoring data, regularly assess and adjust the building's energy efficiency to ensure that the building maintains optimal energy efficiency under different seasons, environmental changes and usage needs.

2. The energy consumption optimization method integrating building structural parameters according to claim 1, characterized in that, Through intelligent sensors and building information modeling systems, real-time data on building geometry, envelope, equipment configuration, human activity, and external environment are collected, including the following sub-steps: S101. By deploying smart sensors inside the building, environmental data such as temperature, humidity, CO2 concentration, human activity, and power load inside and outside the building are collected. S102. Obtain structural data such as the building's geometry, envelope materials, and equipment configuration through a building information modeling system, and integrate and analyze this data with data collected by sensors.

3. The energy consumption optimization method integrating building structural parameters according to claim 1, characterized in that, Based on the collected data, the building's heat load and energy consumption distribution are calculated using building energy efficiency analysis tools, and building energy efficiency performance indicators are extracted to establish a building energy efficiency baseline model, including the following sub-steps: S201. Calculate the internal and external heat loads of a building using building energy efficiency simulation tools, taking into account the heat conduction characteristics of the building envelope and the loads of equipment and personnel activities within the building. S202. Based on the heat load calculation results, extract the building's energy efficiency performance indicators and establish a building energy efficiency baseline model based on these indicators.

4. The energy consumption optimization method for integrated building structural parameters according to claim 1, characterized in that, Based on the energy efficiency baseline model, adaptive building envelope technology is used to dynamically adjust the thermal performance of the building envelope to adapt to external climate change and internal heat load demand, including the following sub-steps: S301. Evaluate the thermal performance of building envelopes such as facades, windows, and walls based on the energy efficiency baseline model, and adjust the design of the building envelope according to external climate conditions and building load requirements. S302. Utilize adaptive materials to dynamically adjust the thermal conductivity of the building envelope, enabling the building to optimize its heat load under different seasons and environmental conditions.

5. The energy consumption optimization method for integrated building structural parameters according to claim 1, characterized in that, Based on the optimized building envelope characteristics, the energy recovery system is activated to utilize waste heat generated inside the building and airflow energy, converting them into usable energy for the building system. This includes the following sub-steps: S401. Based on the optimized thermal performance of the building envelope, calculate the waste heat generated inside the building and activate the heat recovery system to recover the waste heat. S402. Activate the airflow energy recovery device to convert the airflow energy generated by air conditioning, ventilation systems, etc., into heat or electricity to supplement the building's energy needs.

6. The energy consumption optimization method integrating building structural parameters according to claim 1, characterized in that, By combining real-time feedback on energy efficiency data and building equipment status, intelligent scheduling strategies for building equipment operation are implemented to optimize building energy efficiency, reduce unnecessary energy consumption, and improve comfort. This includes the following sub-steps: S501. Monitor the operating status of building equipment in real time through the intelligent scheduling system, and adjust the operating parameters of the equipment according to the external environment and indoor needs; S502. Based on data such as temperature and humidity and human activity within the building, dynamically adjust the operating status of building equipment to optimize energy use and improve comfort.

7. The energy consumption optimization method for integrated building structural parameters according to claim 1, characterized in that, Based on adjusted equipment operation strategies and real-time energy efficiency monitoring data, regularly assess and adjust building energy efficiency to ensure that buildings maintain optimal energy efficiency under different seasons, environmental changes, and usage demands. This includes the following sub-steps: S601. By combining real-time feedback energy efficiency monitoring data and the operating status of building equipment, the energy efficiency of the building is regularly assessed to identify areas for optimization. S602. Adjust the operating parameters and system configuration of building equipment according to the energy efficiency assessment results to ensure that the building maintains optimal energy efficiency during long-term operation.

8. An energy consumption optimization system integrating building structural parameters, characterized in that, include: The data acquisition module is used to collect data on the building's geometry, envelope, equipment configuration, personnel activities, and external environment in real time through an intelligent sensor network and a building information modeling system. The energy efficiency analysis module is used to calculate the building's heat load and energy consumption distribution based on the collected data, using building energy efficiency analysis tools, and to extract building energy efficiency performance indicators and establish a building energy efficiency baseline model. The adaptive building envelope adjustment module is used to dynamically adjust the thermal performance of the building envelope based on the energy efficiency baseline model to adapt to external climate change and internal heat load demand. The energy recovery module is used to activate the energy recovery system based on the optimized building envelope characteristics, and to convert the waste heat and airflow energy generated inside the building into usable energy for the building system. The equipment scheduling module is used to combine real-time feedback energy efficiency data and building equipment status to intelligently schedule the operation strategy of building equipment in order to optimize building energy efficiency, reduce unnecessary energy consumption, and improve comfort. The energy efficiency assessment module is used to periodically assess and adjust building energy efficiency based on adjusted equipment operation strategies and real-time energy efficiency monitoring data, ensuring that buildings maintain optimal energy efficiency under different seasons, environmental changes, and usage demands.

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