A natural ventilation factor-based green building design ventilation and lighting optimization system

Abstract

The application relates to the technical field of architectural design optimization, in particular to a green building design ventilation and lighting optimization system based on natural ventilation factors, which comprises a data acquisition unit used for acquiring data of a building site to obtain a basic environment data set, wherein the basic environment data set comprises at least one local dominant wind direction, corresponding wind speed and annual sun running track data; and a direction positioning unit used for generating an annual sun irradiation direction diagram based on the annual sun running track data in the basic environment data set, extracting directions above an illumination intensity threshold value through the annual sun irradiation direction diagram to form at least one sun irradiation key direction. The application can scientifically calculate the most suitable ventilation and lighting scheme by combining the local climate, terrain and functional requirements of the building, maximally utilize natural resources, reduce the dependence on artificial energy, and rationally design the distribution of windows according to the lighting and ventilation requirements of different functional areas.

Description

Technical Field

[0001] This invention relates to the field of building design optimization technology, specifically to a green building design ventilation and lighting optimization system based on natural ventilation factors. Background Technology

[0002] With the intensification of global climate change and the increasing scarcity of energy resources, the construction sector urgently needs to reduce its reliance on traditional energy sources. Traditional buildings often rely on air conditioning and artificial lighting to regulate the indoor environment, which not only increases energy consumption but also has a negative impact on the environment, increasing carbon emissions.

[0003] Currently, improving indoor air quality and comfort is an important issue in modern architectural design. Natural ventilation and sufficient lighting can effectively improve indoor air quality, reduce the accumulation of air pollutants, and enhance the comfort and health of the living or working environment. The window design of traditional building systems is often fixed and cannot be adjusted according to the individual needs of different residents. Furthermore, traditional architectural designs often lack consideration for optimizing space, resulting in low space utilization. For example, the layout of windows and ventilation systems may not be reasonable enough, leading to poor lighting and ventilation in some spaces, and the indoor environment may not be comfortable.

[0004] In addition, traditional building systems often rely on artificial energy sources, such as air conditioning, heating, and artificial lighting, to regulate indoor temperature and light. This not only increases energy consumption but also leads to higher carbon emissions, failing to effectively reduce the environmental burden of buildings. Summary of the Invention

[0005] To achieve the above objectives, the present invention provides the following technical solution: a green building design ventilation and lighting optimization system based on natural ventilation factors, comprising:

[0006] The data acquisition unit is used to collect data from the construction site to obtain a basic environmental dataset, wherein the basic environmental dataset includes at least one prevailing wind direction, corresponding wind speed, and annual solar trajectory data.

[0007] The orientation positioning unit is used to generate an annual solar illumination direction map based on the annual solar trajectory data in the basic environmental dataset, extract directions above the light intensity threshold through the annual solar illumination direction map, and form at least one key solar illumination direction; obtain the building's lighting and ventilation requirements, wherein the lighting requirements include the light intensity requirements of each functional area, and the ventilation requirements include the air circulation rate requirements of each functional area;

[0008] The occlusion recognition unit is used to collect terrain data of the building site, identify terrain occlusion based on the terrain data, the terrain occlusion includes the height of the occluding object and the occlusion range; and correct the prevailing wind direction and wind speed in the basic environmental dataset in combination with the terrain occlusion, and calculate the ventilation coefficient of the prevailing wind direction, the ventilation coefficient is used to characterize the actual available ventilation efficiency.

[0009] The location design unit is used to correct the light intensity of the key direction of solar illumination in combination with the terrain shading, calculate the light coefficient of the key direction of solar illumination, the light coefficient reflecting the actual available light efficiency; and conduct preliminary location design of building windows based on the ventilation coefficient of the prevailing wind direction, the light coefficient of the key direction of solar illumination, and the lighting and ventilation requirements, and determine the candidate distribution area of ​​windows.

[0010] The ventilation optimization unit is used to acquire data on people's habits regarding window layout, including preferred window locations in frequently used activity areas and location characteristics related to window opening frequency. The unit then uses this data to adjust the candidate distribution areas of windows to obtain the final architectural window location design scheme.

[0011] Preferably, data is collected from the building site to obtain a basic environmental dataset, including:

[0012] The wind direction and wind speed data of the construction site are collected by meteorological monitoring equipment within a continuous preset period. At least one wind direction with the highest frequency is selected as the dominant wind direction, and the average wind speed and wind speed fluctuation range corresponding to each dominant wind direction are recorded.

[0013] The latitude, longitude, and altitude data of the building site are obtained by using solar monitoring equipment or astronomical algorithms. Combined with the Earth's orbital trajectory, the solar altitude angle and azimuth angle at different times of the year are calculated to form the annual solar orbital trajectory data.

[0014] The dominant wind direction, corresponding wind speed data, and annual solar trajectory data are integrated to establish a basic environmental dataset.

[0015] Preferably, based on the annual solar trajectory data in the basic environmental dataset, an annual solar illumination direction map is generated. Directions above a certain light intensity threshold are extracted from the annual solar illumination direction map to form at least one key solar illumination direction, including:

[0016] Based on the annual solar trajectory data, the solar illumination direction sub-maps for each time period are generated by dividing the time period into seasons or months, and the sub-maps are integrated to form an annual solar illumination direction map.

[0017] Set a light intensity threshold corresponding to the building function, extract the directions whose light intensity exceeds the threshold in each time period from the annual solar radiation direction map, and count the occurrence duration and cumulative light intensity of each direction;

[0018] The directions with the highest cumulative light intensity are determined as the key directions of solar radiation.

[0019] Preferably, the building's lighting and ventilation requirements are obtained, including:

[0020] The building is divided into functional areas according to its intended use. These functional areas include office areas, residential areas, and public activity areas.

[0021] For each functional area, the minimum light intensity and duration requirements for each area are determined in combination with building design codes and user needs, thus obtaining the lighting requirements;

[0022] For each functional area, the minimum air circulation rate and ventilation duration requirements are determined based on indoor air quality standards and human comfort requirements, thus obtaining the ventilation needs.

[0023] Preferably, the process involves collecting terrain data of the building site and identifying terrain occlusion based on the terrain data, including:

[0024] Acquire terrain elevation data of the building site and its surrounding preset area, and generate a 3D terrain model;

[0025] Identify obstructions from the three-dimensional terrain model, including mountains, adjacent buildings, and trees, and record the height, distance from the building site, and distribution range of each obstruction.

[0026] Based on the height and distance of the obstructions, the obstruction angle and obstruction area of ​​each obstruction on the building site at different times are calculated to obtain the terrain obstruction situation.

[0027] Preferably, the prevailing wind direction and speed in the basic environmental dataset are corrected based on the terrain shading, and the ventilation coefficient of the prevailing wind direction is calculated, including:

[0028] Based on the distribution range and height of the obstructions in the terrain obstruction situation, the drag coefficient for each prevailing wind direction is calculated, and the drag coefficient is positively correlated with the density and height of the obstructions;

[0029] The wind speed corresponding to the prevailing wind direction is corrected using the aforementioned drag coefficient to obtain the effective wind speed actually reaching the building site.

[0030] The ventilation coefficient of the prevailing wind direction is obtained by multiplying the effective wind speed by the frequency of occurrence of the prevailing wind direction.

[0031] Preferably, the illuminance of the key direction of solar illumination is corrected based on the terrain shading, and the illuminance coefficient of the key direction of solar illumination is calculated, including:

[0032] Based on the shading angle and shading area in the terrain shading situation, determine the proportion of time that each key direction of solar illumination is blocked at different times.

[0033] Based on the shading duration ratio, the original light intensity of each key solar radiation direction is attenuated to obtain the effective light intensity that can actually reach the building site.

[0034] The illuminance coefficient of the key direction of solar illumination is obtained by weighting and fusing the effective light intensity with the duration of occurrence of the key direction of solar illumination.

[0035] Preferably, based on the ventilation coefficient of the prevailing wind direction, the illuminance coefficient of the key direction of solar radiation, and in conjunction with the lighting and ventilation requirements, a preliminary design for the location of building windows is carried out to determine candidate distribution areas for windows, including:

[0036] The building facade is divided into areas according to its orientation, and the ventilation coefficient of the prevailing wind direction and the light coefficient of the key direction of solar radiation are calculated for each area.

[0037] For each functional area, an exterior facade area with a light coefficient that meets the standard is matched according to its lighting requirements, and an exterior facade area with a ventilation coefficient that meets the standard is matched according to its ventilation requirements.

[0038] The exterior facade areas where both the illumination coefficient and ventilation coefficient meet the standards are selected as candidate distribution areas for windows, and the priority of each candidate area is marked. The priority is positively correlated with the degree of compliance of the coefficients.

[0039] Preferably, data on people's habits regarding window layouts is obtained, including:

[0040] Through user surveys, we collected activity trajectory data of users in various functional areas of similar buildings to identify commonly used activity areas.

[0041] Statistics were compiled on users' preferences for window locations within frequently used activity areas, including the distance between the window and the activity point and its relative orientation.

[0042] By analyzing the frequency of window opening in different seasons and time periods, and correlating the relationship between window location and opening frequency, data on people's habitual window layout can be obtained.

[0043] Preferably, the candidate distribution area of ​​the windows is adjusted using the data on the people's habitual window layout to obtain the final architectural window position design scheme, including:

[0044] The preferred window locations of frequently used activity areas in the habitual data are matched with candidate distribution areas, and the locations of mismatched candidate areas are fine-tuned.

[0045] Based on the location characteristics associated with window opening frequency, the window size and opening method of the candidate distribution area are optimized;

[0046] Verify whether the adjusted window positions still meet the maximum requirements for lighting and ventilation. If they do, the final window position design will be adopted. If not, the window positions will be fine-tuned until they are met.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] (1) By combining local climate, topography and functional requirements of buildings, this invention can scientifically calculate the most suitable ventilation and lighting scheme, maximize the use of natural resources, reduce dependence on artificial energy, and rationally design the distribution of windows according to the lighting and ventilation requirements of different functional areas. This not only optimizes lighting and air circulation, but also ensures the comfort and health of the indoor environment. Furthermore, by identifying and correcting the topographic obstruction of the building site, the ventilation coefficient of the prevailing wind direction and the light coefficient of the key direction of solar radiation are calculated to ensure that the building design can make the most of natural ventilation and lighting and improve energy efficiency.

[0049] (2) By analyzing data on people’s habits, the system can optimize the layout and opening method of windows according to users’ window preferences and window opening habits, making the building design more in line with the actual user’s needs, improving the quality of life. Furthermore, by optimizing the design of natural ventilation and lighting, the use of air conditioning and artificial lighting is reduced, thereby reducing the building’s energy consumption and carbon emissions, meeting the requirements of green building and sustainable development. The window design is based on the functional requirements of the building, which not only meets the needs of lighting and ventilation, but also improves the utilization rate of space and the diversity of functions. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the overall system architecture in one embodiment of the present invention.

[0051] In the diagram: 1. Data acquisition unit; 2. Direction positioning unit; 3. Occlusion recognition unit; 4. Position design unit; 5. Ventilation optimization unit. Detailed Implementation

[0052] 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 embodiments of the present invention, and not all embodiments. 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.

[0053] Example 1, please refer to Figure 1 This invention provides a technical solution: a green building design ventilation and lighting optimization system based on natural ventilation factors, comprising:

[0054] Data acquisition unit 1 is used to collect data from the building site to obtain a basic environmental dataset, which includes at least one prevailing wind direction, corresponding wind speed, and annual solar trajectory data.

[0055] Direction positioning unit 2 is used to generate an annual solar illumination direction map based on the annual solar trajectory data in the basic environmental dataset, extract directions above the light intensity threshold from the annual solar illumination direction map, and form at least one key solar illumination direction; obtain the building's lighting and ventilation requirements, including the light intensity requirements of each functional area and the air circulation rate requirements of each functional area.

[0056] The occlusion recognition unit 3 is used to collect terrain data of the building site, identify terrain occlusion based on the terrain data, including the height of the occlusion object and the occlusion range; and correct the prevailing wind direction and wind speed in the basic environmental dataset in combination with the terrain occlusion, and calculate the ventilation coefficient of the prevailing wind direction. The ventilation coefficient is used to characterize the actual available ventilation efficiency.

[0057] Location design unit 4 is used to correct the light intensity of the key direction of solar radiation in combination with the terrain shading, calculate the light coefficient of the key direction of solar radiation, and the light coefficient reflects the actual available light efficiency; based on the ventilation coefficient of the prevailing wind direction and the light coefficient of the key direction of solar radiation, combined with the lighting and ventilation requirements, the preliminary location design of the building windows is carried out to determine the candidate distribution area of ​​the windows.

[0058] Ventilation optimization unit 5 is used to obtain habitual data on window layout of people. The habitual data includes the preferred window locations in frequently used activity areas and the location characteristics related to the frequency of window opening. The candidate distribution areas of windows are adjusted using the habitual data on window layout of people to obtain the final architectural window location design scheme.

[0059] It's important to note that by collecting basic environmental data, including local wind direction, wind speed, and the sun's annual trajectory, the system provides data support for subsequent design and analysis. For example, the system collects the strongest wind direction and speed of a location throughout the year, as well as the direction and intensity of sunlight at different times of day. For instance, assuming the building is located in a windy city, the system will collect data showing that the prevailing wind direction is northeast with high wind speeds, and will also record the strong sunlight entering from the south during winter. Based on the collected data, a year-round solar radiation map is generated to determine which directions receive sufficient light intensity. Simultaneously, it considers the building's lighting needs (the required light intensity for different areas) and ventilation needs (the required airflow rate for each area). For example, if the building's office areas require strong natural light, the system will identify that the southeast direction has the strongest sunlight, thus recommending that office windows face this direction. By analyzing the surrounding terrain, the system identifies potential obstructions (such as nearby buildings, hills, etc.), which can affect wind speed and light intensity. Therefore, the system will correct the original wind direction and lighting data to calculate the actual ventilation and lighting efficiency. For example, if there is a tall building near the building, located in the northwest, blocking the wind from the northwest, the system will take this factor into account and calculate that the actual wind speed may be lower than expected. Based on the corrected wind direction and lighting direction data, the system designs the window positions of the building. The system takes into account the lighting and ventilation needs of each area and initially determines the distribution area of ​​windows. For example, if the system calculates that the wind speed in the southwest is lower and the sunlight in the southeast is stronger, it may design office windows in the southeast and kitchen windows in the northeast to ensure that the needs of ventilation and lighting are met. In the final window design, the system will also use human habit data (such as residents' window opening frequency, preferred window positions, etc.) to adjust the window layout. This can make the building more in line with the habits and needs of residents and improve comfort. For example, if residents usually prefer to open windows in the evening, the system may increase the number of windows in a frequently used area to provide better air circulation at the appropriate time.

[0060] In one alternative embodiment, data is collected from the building site to obtain a basic environmental dataset, including:

[0061] The wind direction and wind speed data of the construction site are collected by meteorological monitoring equipment within a continuous preset period. At least one wind direction with the highest frequency is selected as the dominant wind direction, and the average wind speed and wind speed fluctuation range corresponding to each dominant wind direction are recorded.

[0062] The latitude, longitude, and altitude data of the building site are obtained by using solar monitoring equipment or astronomical algorithms. Combined with the Earth's orbital trajectory, the solar altitude angle and azimuth angle at different times of the year are calculated to form the annual solar orbital trajectory data.

[0063] By integrating the prevailing wind direction, corresponding wind speed data, and annual solar trajectory data, a basic environmental dataset is established.

[0064] It should be noted that meteorological equipment is used to collect wind speed and direction data for the construction site within a preset period. The equipment records wind speed and direction for each time period to help understand wind variation patterns. For example, at a construction site, the meteorological monitoring equipment records that the prevailing wind direction is southeast, with an average wind speed of 3 m / s and a fluctuation range of 2 to 4 m / s. This data can help designers optimize building shapes and use wind direction to reduce air conditioning energy consumption. The most common wind direction can be identified from the wind direction data as a reference in architectural design. The most frequently occurring wind direction can be identified to optimize building ventilation design. For example, if southeast winds occur most frequently throughout the year, then southeast winds are the prevailing wind direction for this construction area. After determining the prevailing wind direction, the data is recorded. Upward wind speed and its fluctuation range are crucial for accurately designing a building's ventilation system. For example, if the prevailing wind direction is southeast, the recorded wind speed is 3 m / s, fluctuating between 2 and 4 m / s. Designers can use this data to consider window openings and ventilation systems. Using solar monitoring equipment or astronomical algorithms, combined with the building site's latitude, longitude, and altitude, the annual solar altitude and azimuth angles can be calculated. The sun's trajectory changes annually, and designers need to know the sun's angle at different times of day to design the building's lighting system. For example, at a certain building location, the sun's altitude angle is 75 degrees and its azimuth angle is 180 degrees (south) at midday in summer. This data helps designers rationally arrange windows to ensure optimal lighting.

[0065] In an optional embodiment, based on the annual solar trajectory data in the basic environmental dataset, an annual solar illumination direction map is generated. Directions above a certain light intensity threshold are extracted from the annual solar illumination direction map to form at least one key solar illumination direction, including:

[0066] Based on the annual solar trajectory data, the solar illumination direction sub-maps are generated by dividing the time period by season or month, and the sub-maps are integrated to form the annual solar illumination direction map.

[0067] Set the light intensity threshold corresponding to the building function, extract the directions with light intensity exceeding the threshold in each time period from the annual solar radiation direction map, and count the occurrence duration and cumulative light intensity of each direction.

[0068] The directions with the highest cumulative light intensity are determined as the key directions of solar radiation.

[0069] It should be noted that, based on the sun's trajectory, sub-maps of solar illumination direction for different seasons or months are generated, ultimately forming a year-round solar illumination direction map. The direction and intensity of sunlight vary across seasons, thus requiring adjustments to the building's lighting system over time. For example, the sun is lower in winter, and its angle may be closer to the ground, while it is higher in summer. Designers can use this information to plan the building's shading design. A standard for light intensity is set based on the building's functional requirements, and the required solar illumination direction is extracted. Different areas have different light intensity requirements; designers can choose the direction with the highest light intensity during the day for architectural design. For example, office areas require higher light intensity, and designers might choose south-facing windows with direct sunlight as the primary lighting direction. The direction with the highest solar illumination intensity is selected from the year-round solar illumination direction map as the building's key direction. Based on the year-round solar illumination data, the most common and strongest light directions are determined. For example, if the south-facing direction has the highest cumulative light intensity throughout the year, then the south-facing direction is the building's key lighting direction.

[0070] In one alternative embodiment, obtaining the building's lighting and ventilation requirements includes:

[0071] The building is divided into functional areas according to its intended use. These functional areas include office areas, residential areas, and public activity areas.

[0072] For each functional area, the minimum light intensity and duration requirements for each area are determined in combination with building design codes and user needs, thus obtaining the lighting requirements;

[0073] For each functional area, the minimum air circulation rate and ventilation duration requirements are determined based on indoor air quality standards and human comfort requirements, thus obtaining the ventilation needs.

[0074] It should be noted that functional zoning is performed based on the building's intended use (e.g., office area, residential area, and public activity area); the building space is divided into multiple zones, each with different needs, thus requiring different lighting and ventilation. For example, office areas require strong lighting, while residential areas prioritize privacy and comfortable ventilation. Minimum lighting intensity and duration requirements are determined based on the lighting needs of different functional areas. Minimum lighting intensity and duration for each zone are calculated according to building codes and usage requirements. For example, office areas may require a minimum solar intensity of 200 lx (lux) and at least 4 hours of illumination. Minimum airflow rate and ventilation duration are determined for each zone based on indoor air quality standards and human comfort requirements. The building's ventilation system design must consider airflow rate and ventilation time to ensure indoor air quality meets standards. For example, residential areas require an airflow rate of 0.5 m / s and a ventilation duration of at least 10 hours per day to ensure fresh air.

[0075] In one optional embodiment, topographic data of the building site is collected, and topographic occlusion is identified based on the topographic data, including:

[0076] Acquire terrain elevation data of the building site and its surrounding preset area, and generate a 3D terrain model;

[0077] Identify occlusions from the 3D terrain model, including mountains, adjacent buildings, and trees, and record the height, distance from the building site, and distribution range of each occlusion.

[0078] Based on the height and distance of the obstructions, the obstruction angle and obstruction area of ​​each obstruction on the building site at different times are calculated to obtain the terrain obstruction situation.

[0079] It should be noted that digital elevation models (DEMs), lidar (LiDAR), or geographic information systems (GIS) data are used to obtain elevation information of the site and surrounding terrain. This elevation data is then converted into a three-dimensional terrain model to facilitate subsequent analysis of obstructions, ventilation, and lighting. For example, in a building site in a valley with undulating hills, a 3D terrain model generated using LiDAR scanning clearly shows a 50-meter-high mountain on the east side of the site. The 3D terrain model is analyzed to identify obstacles that may block wind and sunlight. For each obstruction, its height, distance from the building site, and distribution range on the terrain are recorded. For example, if there is a 30-meter-high residential building on the west side of the site and a 10-meter-high tree belt on the east side, this data is recorded to calculate the obstruction of wind and sunlight.

[0080] In an optional embodiment, the prevailing wind direction and speed in the basic environmental dataset are corrected based on terrain shading, and the ventilation coefficient for the prevailing wind direction is calculated, including:

[0081] Based on the distribution range and height of the obstructions in the terrain obstruction situation, the wind resistance coefficient in each prevailing wind direction is calculated. The wind resistance coefficient is positively correlated with the density and height of the obstructions.

[0082] By using the drag coefficient to correct the wind speed corresponding to the prevailing wind direction, the effective wind speed actually reaching the building site can be obtained.

[0083] The ventilation coefficient of the prevailing wind direction is obtained by multiplying the effective wind speed by the frequency of occurrence of the prevailing wind direction.

[0084] It should be noted that the shading angle refers to the ratio of the height of an obstacle to its distance as seen from the building site (angle of elevation); the shading area refers to the proportion of the horizontal area where the sun or wind is blocked; it can be calculated by time period (e.g., hourly within a day) to obtain the dynamic shading effect; for example, a mountain on the east side will block the sun at a 20° elevation angle at 9 am, accounting for 40% of the ground lighting area; at 3 pm, the mountain's shading angle decreases, and the shading area is only 10%. The drag coefficient is used to represent the degree to which an obstacle hinders wind speed; taller and denser obstacles have a greater drag coefficient; closer obstacles have a more significant impact; for example, a tall building on the west side has a drag coefficient of 0.4, while a sparsely located obstacle on the east side has a greater drag coefficient. A wind resistance coefficient of 0.1 for sparse trees indicates that the buildings on the west side block more wind. The wind speed in the original meteorological data is corrected by multiplying it by (1 - wind resistance coefficient) to obtain the actual wind speed after passing through the obstruction. For example, if the prevailing wind direction is southeast, the original wind speed is 4 m / s, and the wind resistance coefficient of the trees on the east side is 0.1, then the effective wind speed = 4 × (1 - 0.1) = 3.6 m / s. The ventilation coefficient = effective wind speed × frequency of wind direction. It is a comprehensive evaluation of the actual ventilation capacity of the building site under different wind directions throughout the year. For example, if the effective wind speed of the southeast wind is 3.6 m / s and the frequency of the southeast wind throughout the year is 0.3, then the ventilation coefficient = 3.6 × 0.3 = 1.08 m / s·frequency of occurrence.

[0085] In an optional embodiment, the illuminance of the key direction of solar illumination is corrected based on terrain shading, and the illuminance coefficient of the key direction of solar illumination is calculated, including:

[0086] Based on the shading angle and shading area in the terrain shading situation, determine the proportion of time that each key direction of solar illumination is blocked at different times.

[0087] The attenuation of the original light intensity in each key direction of solar radiation is calculated based on the proportion of shading duration to obtain the effective light intensity that can actually reach the building site.

[0088] The illuminance coefficient of the key direction of solar illumination is obtained by weighting and fusing the effective light intensity with the duration of occurrence of the key direction of solar illumination.

[0089] It should be noted that by calculating the solar illumination angle for each time period (e.g., every hour), the proportion of time the sun is blocked by the obstruction is determined. For example, in a key south-facing lighting direction, the sun is blocked by a tall building to the west from 10:00 AM to 12:00 PM, accounting for 50% of the total time during that period. Effective illuminance = Original illuminance × (1 - Obstruction proportion). The larger the obstruction proportion, the less actual sunlight reaches the site. For example, if the original illuminance is 500 W / m², and the obstruction proportion is 50% from 10:00 AM to 12:00 PM, the effective illuminance = 500 × (1 - 0.5) = 250 W / m². Illuminance coefficient = ∑ (Effective illuminance per time period × Time weight) / Total duration of the year. Taking into account both solar intensity and the time of obstruction, an annual illuminance evaluation index is obtained. For example, the illuminance coefficient of 0.7 is obtained by weighting the effective illuminance of the south-facing direction by time period, indicating that 70% of the ideal sunlight can be utilized in this direction throughout the year.

[0090] In one alternative embodiment, based on the ventilation coefficient of the prevailing wind direction and the illuminance coefficient of the key direction of solar radiation, combined with lighting and ventilation requirements, a preliminary design for the location of building windows is carried out to determine candidate distribution areas for windows, including:

[0091] The building facade is divided into areas according to its orientation, and the ventilation coefficient of the prevailing wind direction and the light coefficient of the key direction of solar radiation are calculated for each area.

[0092] For each functional area, an exterior facade area with a light coefficient that meets the standard is matched according to its lighting requirements, and an exterior facade area with a ventilation coefficient that meets the standard is matched according to its ventilation requirements.

[0093] The exterior facade areas where both the illumination coefficient and ventilation coefficient meet the standards are selected as candidate distribution areas for windows, and the priority of each candidate area is marked. The priority is positively correlated with the degree of compliance of the coefficients.

[0094] It should be noted that, based on the building's orientation, the building facade is divided into multiple zones. For each zone, the ventilation coefficient under the prevailing wind direction and the illuminance coefficient under the key direction of solar radiation are calculated. The wind direction ventilation coefficient is primarily adjusted for ventilation effectiveness based on wind resistance and wind speed. The illuminance coefficient is calculated based on the illuminance intensity and shading conditions of each zone. For example, a south-facing facade is identified as the primary lighting area, with a southeast wind direction; this area has an illuminance coefficient of 0.75 and a wind speed-adjusted ventilation coefficient of 1.2. Each functional area (such as the living room, bedroom, and office) has different lighting and ventilation requirements. Based on the calculated illuminance and ventilation coefficients, facade areas meeting the requirements are matched with the functional areas. Lighting requirements: Sufficient sunlight is required. For areas requiring good ventilation (such as living rooms), areas with higher illuminance coefficients are prioritized. For areas requiring good ventilation (such as bedrooms), areas with higher ventilation coefficients are prioritized. For example, living rooms have higher illuminance requirements, and the suitable exterior facade area is south-facing with an illuminance coefficient greater than 0.7; bedrooms have higher ventilation requirements, and the suitable exterior facade area is east-facing with higher wind speeds. Considering both illuminance and ventilation requirements, candidate window distribution areas are selected from the compliant exterior facade areas. The priority of each area is determined by the illuminance and ventilation coefficients, with areas having better illuminance and ventilation having higher priority. For example, south-facing and east-facing facades are identified as priority areas for illuminance and ventilation, respectively. The south-facing illuminance coefficient is 0.75, and the east-facing ventilation coefficient is 1.2, therefore these two areas are prioritized for window locations.

[0095] In one optional embodiment, obtaining user habit data regarding window layout includes:

[0096] Through user surveys, we collected activity trajectory data of users in various functional areas of similar buildings to identify commonly used activity areas.

[0097] Statistics were compiled on users' preferences for window locations within frequently used activity areas, including the distance between the window and the activity point and its relative orientation.

[0098] By analyzing the frequency of window opening in different seasons and time periods, and correlating the relationship between window location and opening frequency, data on people's habitual window layout can be obtained.

[0099] It's important to note that user surveys and data collection are used to understand the location and activity types of frequently used areas within the building; for example, which areas are commonly used for meetings, entertainment, and rest. These activity areas will influence the choice of window location, and windows need to meet the lighting and ventilation requirements of these areas. For instance, surveys show that office areas and meeting rooms are areas with frequent personnel activity, while bedrooms are used less frequently; office areas are located on the south side of the building, while meeting rooms are located on the east side. Surveys and interviews are also conducted to understand user preferences regarding windows; for example, do users prefer windows to be close to activity areas, or does the orientation of windows affect their comfort? Moderation is key; collecting this data can help optimize window layout; for example, surveys show that users prefer windows near their desks, ideally facing a direction with ample natural light, such as south; analyzing the frequency with which users open windows in different seasons and at different times helps determine which windows are easier to open and which locations require better ventilation or larger opening areas; optimizing window layout is not only for lighting and ventilation but also for meeting users' actual window opening needs; for example, in summer, users tend to open windows in the morning and evening, while in winter they mainly open them during the day, especially in office areas; south-facing windows are opened more frequently.

[0100] In an optional embodiment, the candidate distribution areas of windows are adjusted using data on people's habits regarding window layouts to obtain a final architectural window location design scheme, including:

[0101] The preferred window locations of frequently used activity areas in the habitual data are matched with candidate distribution areas, and the locations of mismatched candidate areas are fine-tuned.

[0102] Based on the location characteristics associated with window opening frequency, the window size and opening method of the candidate distribution area are optimized;

[0103] Verify whether the adjusted window positions still meet the maximum requirements for lighting and ventilation. If they do, the final window position design will be adopted. If not, the window positions will be fine-tuned until they are met.

[0104] It's important to note that the process involves matching users' window preferences with candidate areas in the architectural design to identify locations that don't align with user habits. Based on this feedback, window positions are fine-tuned to better suit actual needs. For example, if a user prefers a window near their desk, but the candidate window locations don't match the office area, the window position may need to be adjusted to be closer to the desk. Based on window opening frequency data, the size and opening method of windows in different locations are determined. Ventilation efficiency and user habits need to be considered to optimize window design. For instance, areas with higher ventilation needs may require larger or operable windows. Office and meeting room windows require larger opening areas, while bedroom windows can be smaller and designed as sliding windows to save space. The final step is to verify whether the fine-tuned window positions still meet lighting and ventilation requirements. If not, further adjustments are made until the optimal solution is found. For example, if the adjusted window position ensures that both the living room and bedroom meet lighting and ventilation requirements while maximizing user window opening habits, then this location is ultimately selected as the design solution.

[0105] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A green building design ventilation and lighting optimization system based on natural ventilation factors, characterized in that, include: The data acquisition unit is used to collect data from the construction site to obtain a basic environmental dataset, wherein the basic environmental dataset includes at least one prevailing wind direction, corresponding wind speed, and annual solar trajectory data. The orientation positioning unit is used to generate an annual solar illumination direction map based on the annual solar trajectory data in the basic environmental dataset, extract directions above the light intensity threshold through the annual solar illumination direction map, and form at least one key solar illumination direction; obtain the building's lighting and ventilation requirements, wherein the lighting requirements include the light intensity requirements of each functional area, and the ventilation requirements include the air circulation rate requirements of each functional area; The occlusion recognition unit is used to collect terrain data of the building site, identify terrain occlusion based on the terrain data, the terrain occlusion includes the height of the occluding object and the occlusion range; and correct the prevailing wind direction and wind speed in the basic environmental dataset in combination with the terrain occlusion, and calculate the ventilation coefficient of the prevailing wind direction, the ventilation coefficient is used to characterize the actual available ventilation efficiency. The location design unit is used to correct the light intensity of the key direction of solar illumination in combination with the terrain shading, calculate the light coefficient of the key direction of solar illumination, the light coefficient reflecting the actual available light efficiency; and conduct preliminary location design of building windows based on the ventilation coefficient of the prevailing wind direction, the light coefficient of the key direction of solar illumination, and the lighting and ventilation requirements, and determine the candidate distribution area of ​​windows. The ventilation optimization unit is used to acquire user habit data on window layout, including preferred window locations in frequently used activity areas and location features related to window opening frequency; the user habit data on window layout is used to adjust the candidate distribution areas of windows to obtain the final building window location design scheme. The process involves adjusting the candidate window distribution areas using data on the individuals' habitual window layouts to obtain the final architectural window location design scheme, including: The preferred window locations of frequently used activity areas in the habitual data are matched with candidate distribution areas, and the locations of mismatched candidate areas are fine-tuned. Based on the location characteristics associated with window opening frequency, the window size and opening method of the candidate distribution area are optimized; Verify whether the adjusted window positions still meet the maximum requirements for lighting and ventilation. If they do, the final window position design will be adopted. If not, the window positions will be fine-tuned until they are met.

2. The green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 1, characterized in that, Data was collected from the building site to obtain a basic environmental dataset, including: The wind direction and wind speed data of the construction site are collected by meteorological monitoring equipment within a continuous preset period. At least one wind direction with the highest frequency is selected as the dominant wind direction, and the average wind speed and wind speed fluctuation range corresponding to each dominant wind direction are recorded. The latitude, longitude, and altitude data of the building site are obtained by using solar monitoring equipment or astronomical algorithms. Combined with the Earth's orbital trajectory, the solar altitude angle and azimuth angle at different times of the year are calculated to form the annual solar orbital trajectory data. The dominant wind direction, corresponding wind speed data, and annual solar trajectory data are integrated to establish a basic environmental dataset.

3. The green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 2, characterized in that, Based on the annual solar trajectory data in the aforementioned basic environmental dataset, an annual solar illumination direction map is generated. Directions above a certain light intensity threshold are extracted from this annual solar illumination direction map to form at least one key solar illumination direction, including: Based on the annual solar trajectory data, the solar illumination direction sub-maps for each time period are generated by dividing the time period into seasons or months, and the sub-maps are integrated to form an annual solar illumination direction map. Set a light intensity threshold corresponding to the building function, extract the directions whose light intensity exceeds the threshold in each time period from the annual solar radiation direction map, and count the occurrence duration and cumulative light intensity of each direction; The directions with the highest cumulative light intensity are determined as the key directions of solar radiation.

4. The green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 3, characterized in that, Obtain the building's lighting and ventilation requirements, including: The building is divided into functional areas according to its intended use. These functional areas include office areas, residential areas, and public activity areas. For each functional area, the minimum light intensity and duration requirements for each area are determined in combination with building design codes and user needs, thus obtaining the lighting requirements; For each functional area, the minimum air circulation rate and ventilation duration requirements are determined based on indoor air quality standards and human comfort requirements, thus obtaining the ventilation needs.

5. A green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 4, characterized in that, Collecting topographic data of the building site and identifying terrain occlusion based on the topographic data includes: Acquire topographic elevation data of the building site and its surrounding preset area, and generate a 3D topographic model; Identify obstructions from the three-dimensional terrain model, including mountains, adjacent buildings, and trees, and record the height, distance from the building site, and distribution range of each obstruction. Based on the height and distance of the obstructions, the obstruction angle and obstruction area of ​​each obstruction on the building site at different times are calculated to obtain the terrain obstruction situation.

6. A green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 5, characterized in that, The prevailing wind direction and speed in the basic environmental dataset are corrected based on the terrain obstruction, and the ventilation coefficient of the prevailing wind direction is calculated, including: Based on the distribution range and height of the obstructions in the terrain obstruction situation, the drag coefficient for each prevailing wind direction is calculated, and the drag coefficient is positively correlated with the density and height of the obstructions; The wind speed corresponding to the prevailing wind direction is corrected using the aforementioned drag coefficient to obtain the effective wind speed actually reaching the building site. The ventilation coefficient of the prevailing wind direction is obtained by multiplying the effective wind speed by the frequency of occurrence of the prevailing wind direction.

7. A green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 6, characterized in that, The illuminance of the key direction of solar illumination is corrected based on the terrain shading, and the illuminance coefficient of the key direction of solar illumination is calculated, including: Based on the shading angle and shading area in the terrain shading situation, determine the proportion of time that each key direction of solar illumination is blocked at different times. The original light intensity of each key direction of solar radiation is attenuated based on the proportion of time that the sun is blocked, so as to obtain the effective light intensity that can actually reach the building site. The illuminance coefficient of the key direction of solar illumination is obtained by weighting and fusing the effective light intensity with the duration of occurrence of the key direction of solar illumination.

8. A green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 7, characterized in that, Based on the ventilation coefficient of the prevailing wind direction and the illuminance coefficient of the key direction of solar radiation, combined with the lighting and ventilation requirements, a preliminary design for the location of building windows is carried out to determine the candidate distribution areas for windows, including: The building facade is divided into areas according to its orientation, and the ventilation coefficient of the prevailing wind direction and the light coefficient of the key direction of solar radiation are calculated for each area. For each functional area, an exterior facade area with a light coefficient that meets the standard is matched according to its lighting requirements, and an exterior facade area with a ventilation coefficient that meets the standard is matched according to its ventilation requirements. The exterior facade areas where both the illumination coefficient and ventilation coefficient meet the standards are selected as candidate distribution areas for windows, and the priority of each candidate area is marked. The priority is positively correlated with the degree of compliance of the coefficients.

9. A green building design ventilation and lighting optimization system based on natural ventilation factors according to claim 8, characterized in that, Obtain data on people's habits regarding window layouts, including: Through user surveys, we collected activity trajectory data of users in various functional areas of similar buildings to identify commonly used activity areas. Statistics were compiled on users' preferences for window locations within frequently used activity areas, including the distance between the window and the activity point and its relative orientation. By analyzing the frequency of window opening in different seasons and time periods, and correlating the relationship between window location and opening frequency, data on people's habitual window layout can be obtained.

Images