A green building engineering design method

Abstract

The application discloses a green building engineering design method, obtains the construction site of a building engineering, collects geographical environment parameters and meteorological parameters of the construction site, constructs a building design model, inputs the geographical environment parameters and the environment parameters into the building design model for processing, and obtains a building form layout; based on the building form layout, a specific roof layout of the building is obtained, photovoltaic panels and / or small wind-driven generators are erected in the specific roof layout, and a plurality of layout schemes are output; the layout schemes are preliminarily screened based on building constraint conditions; a sparrow search algorithm is used to optimize the preliminarily screened layout schemes, an optimal layout scheme is obtained, the photovoltaic panels and / or the small wind-driven generators are erected based on the optimal layout scheme; a suitable building form layout can be obtained through a deep learning method, and finally, the sparrow search algorithm is introduced to optimize the layout of the photovoltaic panels and the small wind-driven generators, so that the power demand and the green building demand are met.

Description

Technical Field

[0001] This invention relates to the field of building engineering technology, and in particular to a green building engineering design method. Background Technology

[0002] Green building, as an architectural concept aimed at reducing resource consumption, improving resource utilization efficiency, and building a healthy and environmentally friendly living environment, has gradually gained widespread attention. The core of green building lies in the integration of high-tech elements such as greening configuration, natural ventilation, natural lighting, low-energy building envelope, and renewable energy utilization through scientific overall design throughout the entire life cycle of building activities, to achieve a harmonious unity between humanity, architecture, environment, and technology. However, in current green building practices, architectural design schemes are often led by architects. Although corresponding green building technologies are added during the design process, the rationality of green building technical measures is difficult to guarantee due to a lack of comprehensive consideration of environmental factors. The integration of architectural design and performance-based design has also not been effectively achieved. In addition, regarding the utilization of renewable energy in green buildings, the layout of power generation equipment has not been well planned, leading to situations where power generation equipment generates too much or too little electricity. At the same time, the mutual interference between power generation equipment can also significantly reduce the amount of electricity generated. Summary of the Invention

[0003] In view of this, the present invention proposes a green building engineering design method, which obtains the building form and layout through modeling and plans the layout of photovoltaic panels and small wind turbines on the top of the building.

[0004] The technical solution of this invention is implemented as follows:

[0005] A green building engineering design method includes the following steps:

[0006] Step S1: Obtain the construction site of the building project and collect the geographical environment parameters and meteorological parameters of the construction site;

[0007] Step S2: Construct an architectural design model, input geographical and environmental parameters into the architectural design model for processing, and obtain the architectural form and layout;

[0008] Step S3: Obtain the specific roof layout of the building based on the building form layout, install photovoltaic panels and / or small wind turbines in the specific roof layout, and output several layout schemes.

[0009] Step S4: Conduct preliminary screening of layout schemes based on building constraints;

[0010] Step S5: Use the Sparrow Search algorithm to optimize the layout scheme after preliminary screening to obtain the optimal layout scheme, and install photovoltaic panels and / or small wind turbines based on the optimal layout scheme.

[0011] Preferably, the specific steps of step S1 are as follows:

[0012] Step S11: Obtain project planning documents, land transfer contracts, or relevant official documents;

[0013] Step S12: Obtain the specific location of the building construction from the project planning documents, land transfer contract or relevant official documents, and output it as the construction site;

[0014] Step S13: Input the construction location into the geographic information system to obtain geographic environment parameters;

[0015] Step S14: Obtain meteorological parameters of the construction site from the meteorological department's database.

[0016] Preferably, the geographical environmental parameters include terrain slope and elevation difference, soil type, vegetation type and distribution, and water conditions, and the meteorological parameters include average temperature, annual solar altitude angle and azimuth angle, solar radiation intensity, prevailing wind direction and wind speed.

[0017] Preferably, the specific steps of step S2 are as follows:

[0018] Step S21: Obtain green building design schemes as training data. The green building schemes include the building form and layout used in the design, as well as the corresponding geographical environment parameters and meteorological parameters.

[0019] Step S22: Obtain actual constructed green buildings as test data. The actual constructed green buildings include the actual building form and layout, as well as the corresponding geographical environment parameters and meteorological parameters collected in real time.

[0020] Step S23: Construct an architectural design model, train the architectural design model with training data, and after training reaches a preset number of times, test it with test data and calculate the accuracy of the test results.

[0021] Step S24: Stop training when the accuracy of the test results reaches the preset threshold; otherwise, continue training.

[0022] Step S25: Input the collected geographical environment parameters and meteorological parameters of the construction site into the trained architectural design model, and obtain the architectural form and layout after processing.

[0023] Preferably, the building form layout includes building orientation, facade design, functional zoning, door and window openings, building height and number of floors, and specific roof layout.

[0024] Preferably, the specific steps of step S3 are as follows:

[0025] Step S31: Obtain the installation area from the specific layout of the roof, and randomly fill the center of the installation area with photovoltaic panels or small wind turbines;

[0026] Step S32: Extend outward from the center of the installation area and randomly fill it with photovoltaic panels or small wind turbines until the installation area can no longer be filled.

[0027] Step S33: Output the combination of photovoltaic panels and small wind turbines in the installation area as a layout scheme, repeat the above steps, and obtain several layout schemes.

[0028] Preferably, in step S32, when filling photovoltaic panels or small wind turbines, the installation space requirements are obtained based on the model of the photovoltaic panels or small wind turbines, and a suitable distance is selected for filling based on the installation space requirements.

[0029] Preferably, the specific steps of step S4 are as follows:

[0030] Step S41: Analyze the building's electricity demand based on its architectural form and layout;

[0031] Step S42: Evaluate the power generation capacity in all layout options;

[0032] Step S43: Eliminate layout schemes where the power generation capacity cannot meet the building's electricity demand.

[0033] Preferably, the specific steps of step S5 are as follows:

[0034] Step S51: Initialize the sparrow population and determine the number of iterations;

[0035] Step S52: Randomly select a layout scheme and calculate the fitness value of the sparrow based on the lowest cost.

[0036] Step S53: Select another layout scheme, calculate the fitness value, compare it with the previously calculated fitness value, and retain the layout scheme with the largest fitness value.

[0037] Step S54: Perform iterative calculations and output the layout scheme with the highest fitness value as the optimal layout scheme;

[0038] Step S55: Install photovoltaic panels and / or small wind turbines based on the optimal layout scheme.

[0039] Preferably, the number of iterations is the number of layout schemes after preliminary screening.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] ① By collecting data on the construction site of a building project, geographical and meteorological parameters of the construction site can be obtained. Then, the building design model can be constructed to identify the building form and layout. Through big data and machine learning, an accurate building form and layout can be obtained. Compared with relying on architects' experience, the obtained building form and layout are more adapted to the local environment and can better meet green building standards.

[0042] ②After obtaining the building form layout, the specific roof layout will be extracted from the building form layout. Then, photovoltaic panels and / or small wind turbines will be randomly filled in the specific roof layout to form several layout schemes. After preliminary screening, the optimal layout scheme will be found by the sparrow search algorithm. Finally, the optimal layout scheme can not only meet the power generation needs, but also reduce costs. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A flowchart of a green building engineering design method according to the present invention;

[0045] Figure 2 This is a flowchart of step S1 of a green building engineering design method according to the present invention;

[0046] Figure 3 This is a flowchart of step S2 of a green building engineering design method according to the present invention;

[0047] Figure 4 This is a flowchart of step S3 of a green building engineering design method according to the present invention;

[0048] Figure 5 This is a flowchart of step S4 of a green building engineering design method according to the present invention;

[0049] Figure 6 This is a flowchart of step S5 of a green building engineering design method according to the present invention; Detailed Implementation

[0050] To better understand the technical content of this invention, a specific embodiment is provided below, and the invention will be further described in conjunction with the accompanying drawings.

[0051] See Figures 1 to 6 The present invention provides a green building engineering design method, comprising the following steps:

[0052] Step S1: Obtain the construction site of the building project and collect the geographical environment parameters and meteorological parameters of the construction site;

[0053] Step S2: Construct an architectural design model, input geographical and environmental parameters into the architectural design model for processing, and obtain the architectural form and layout;

[0054] Step S3: Obtain the specific roof layout of the building based on the building form layout, install photovoltaic panels and / or small wind turbines in the specific roof layout, and output several layout schemes.

[0055] Step S4: Conduct preliminary screening of layout schemes based on building constraints;

[0056] Step S5: Use the Sparrow Search algorithm to optimize the layout scheme after preliminary screening to obtain the optimal layout scheme, and install photovoltaic panels and / or small wind turbines based on the optimal layout scheme.

[0057] This invention discloses a green building engineering design method for designing the morphological layout of a building at a specific construction site. The designed building meets the requirements of green building in terms of noise reduction, energy conservation, ventilation, and lighting. During the design process, the geographical and meteorological parameters of the construction site are collected first. These parameters significantly impact the building's lighting, ventilation, and noise reduction. Therefore, after collecting these parameters, a building design model is constructed. The model processes the geographical and meteorological parameters to obtain the building's morphological layout. Employing deep learning, the building design model can rapidly integrate and process large amounts of data, obtaining the most suitable morphological layout, including the building's orientation and overall structure. Compared to traditional designs based on architects' experience, this method better meets the requirements of green building and offers faster data processing.

[0058] After obtaining the building's form and layout, the specific layout of the building's roof can be acquired. This allows for the placement of renewable energy equipment on the roof, including solar and wind power, with corresponding equipment such as photovoltaic panels and small wind turbines. The utilization of renewable energy is a crucial aspect of green building; therefore, the placement of photovoltaic panels and small wind turbines on the building's roof is essential. After obtaining the specific roof layout, the photovoltaic panels and / or small wind turbines are randomly placed on the roof, resulting in several layout schemes. To reduce computational load, the layout schemes are initially screened based on constraints. Then, a sparrow search algorithm is used to optimize the initially screened layout schemes, obtaining the optimal layout scheme. Based on the optimal layout scheme, the photovoltaic panels and / or small generators can be deployed. This optimal layout scheme not only meets power generation requirements but also reduces building costs, maximizing the fulfillment of green building requirements.

[0059] Preferably, the specific steps of step S1 are as follows:

[0060] Step S11: Obtain project planning documents, land transfer contracts, or relevant official documents;

[0061] Step S12: Obtain the specific location of the building construction from the project planning documents, land transfer contract or relevant official documents, and output it as the construction site;

[0062] Step S13: Input the construction site into the geographic information system to obtain geographic environmental parameters, including terrain slope and elevation difference, soil type, vegetation type and distribution, and water conditions.

[0063] Step S14: Obtain meteorological parameters of the construction site from the meteorological department's database. The meteorological parameters include average temperature, annual solar altitude angle and azimuth angle, solar radiation intensity, prevailing wind direction and wind speed.

[0064] The specific address of a building is recorded in project planning documents, land transfer contracts, or relevant official documents. Therefore, the corresponding construction site can be found from these documents. In order to obtain the building's form and layout, it is necessary to obtain the geographical environment of the building's surroundings and the meteorological data of the building's location. For geographical environmental parameters, a Geographic Information System (GIS) is used. After finding the specific location of the building from the GIS, the relevant geographical environmental parameters can be directly obtained from the GIS. A reasonable drainage system can be designed according to the terrain, such as using the site slope to build rain gardens or natural drainage channels. The building orientation can be determined according to the climate conditions. In cold regions, the long side of the building can be oriented north and south to obtain more winter sunlight, while in hot regions, shading measures can be considered. If there are ecologically sensitive areas such as wetlands around the site, an ecological buffer zone can be designed to avoid damage and promote coordinated development.

[0065] Meteorological parameters can be obtained directly from meteorological databases. Since green buildings need to consider lighting, ventilation, and the use of renewable energy during construction, obtaining meteorological parameters from meteorological databases can help plan the building's layout. For example, in cold regions, the building's orientation should aim to maximize sunlight exposure to reduce winter heating needs; in hot regions, shading measures should be considered to prevent excessive solar radiation from entering the interior.

[0066] Preferably, the specific steps of step S2 are as follows:

[0067] Step S21: Obtain green building design schemes as training data. The green building schemes include the building form and layout used in the design, as well as the corresponding geographical environment parameters and meteorological parameters.

[0068] Step S22: Obtain actual constructed green buildings as test data. The actual constructed green buildings include the actual building form and layout, as well as the corresponding geographical environment parameters and meteorological parameters collected in real time.

[0069] Step S23: Construct an architectural design model, train the architectural design model with training data, and after training reaches a preset number of times, test it with test data and calculate the accuracy of the test results.

[0070] Step S24: Stop training when the accuracy of the test results reaches the preset threshold; otherwise, continue training.

[0071] Step S25: Input the collected geographical environment parameters and meteorological parameters of the construction site into the trained architectural design model. After processing, the architectural form and layout are obtained. The architectural form and layout includes the building orientation, facade shape, functional zoning, door and window opening layout, building height and number of floors, and specific roof layout.

[0072] After acquiring geographical and meteorological parameters, this invention employs deep learning for data processing and analysis. Currently published green building design schemes are used as training data, while actually constructed green buildings are used as test data. Both training and test data include corresponding building morphology layouts and corresponding geographical and meteorological parameters. The building design model is trained using the training data, continuously updating its recognition performance. After a period of training, the model's accuracy is tested using test data. Training stops when the accuracy reaches a preset threshold, at which point the building design model is ready for practical use. The geographical and meteorological parameters collected in step S1 are input into the building design model, which then processes the data to obtain the corresponding building morphology layout. This layout includes the building's specific structure, orientation, and doorway design, etc. The shape involves the building's planar outline, facade design, and spatial arrangement, such as a regular rectangle, circle, or irregular freeform shape. The orientation specifies the building's location on the site, whether it is north-south, east-west, or another specific angle.

[0073] Preferably, the specific steps of step S3 are as follows:

[0074] Step S31: Obtain the installation area from the specific layout of the roof, and randomly fill the center of the installation area with photovoltaic panels or small wind turbines;

[0075] Step S32: Extend outward from the center of the installation area and randomly fill in photovoltaic panels or small wind turbines in sequence until the installation area can no longer be filled. When filling photovoltaic panels or small wind turbines, obtain their installation space requirements based on the model of the photovoltaic panels or small wind turbines, and select an appropriate distance for filling based on the installation space requirements.

[0076] Step S33: Output the combination of photovoltaic panels and small wind turbines in the installation area as a layout scheme, repeat the above steps, and obtain several layout schemes.

[0077] After obtaining the building's layout, it's necessary to consider how to install photovoltaic panels and small wind turbines on the roof. First, determine the installation area from the specific roof layout. Then, randomly fill the center of the installation area with photovoltaic panels or small wind turbines, extending outwards from the center. This random filling process can create several layout schemes based on the filling order. The number and specific locations of photovoltaic panels and small wind turbines will differ in different layout schemes. In addition, to ensure that each type of power generation equipment can function properly, it's necessary to determine the installation space requirements for photovoltaic panels and small wind turbines. These requirements include the minimum space required for the installation of photovoltaic panels or small wind turbines. When filling, the minimum space must be considered to avoid mutual interference between photovoltaic panels and small wind turbines.

[0078] Preferably, the specific steps of step S4 are as follows:

[0079] Step S41: Analyze the building's electricity demand based on its architectural form and layout;

[0080] Step S42: Evaluate the power generation capacity in all layout options;

[0081] Step S43: Eliminate layout schemes where the power generation capacity cannot meet the building's electricity demand.

[0082] To reduce computational load, after obtaining several layout schemes, a preliminary screening is conducted based on constraints, namely the building's electricity demand. After obtaining the building's electricity demand through building form layout analysis, the power generation capacity of all layout schemes is evaluated. If the power generation capacity cannot meet the building's electricity demand, the corresponding layout scheme is eliminated, reducing the number of layout schemes.

[0083] Preferably, the specific steps of step S5 are as follows:

[0084] Step S51: Initialize the sparrow population and determine the number of iterations. The number of iterations is the number of layout schemes after the initial screening.

[0085] Step S52: Randomly select a layout scheme and calculate the fitness value of the sparrow based on the lowest cost.

[0086] Step S53: Select another layout scheme, calculate the fitness value, compare it with the previously calculated fitness value, and retain the layout scheme with the largest fitness value.

[0087] Step S54: Perform iterative calculations and output the layout scheme with the highest fitness value as the optimal layout scheme;

[0088] Step S55: Install photovoltaic panels and / or small wind turbines based on the optimal layout scheme.

[0089] In practical photovoltaic panel and wind turbine layouts, cost is a key consideration, encompassing not only equipment purchase costs but also installation and maintenance costs. Incorporating cost into fitness value calculations guides optimization towards more economical and efficient layout schemes, avoiding the selection of schemes that, while potentially having acceptable power generation efficiency, are too costly and lack practical application advantages. By calculating the fitness values ​​of all components and conducting a comprehensive comparison, the layout scheme with the highest fitness value can be obtained and output as the optimal layout scheme. The optimal layout scheme not only meets the building's electricity needs but also minimizes building costs, fulfilling the requirements of green building.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A green building engineering design method, characterized in that, Includes the following steps: Step S1: Obtain the construction site of the building project and collect the geographical environment parameters and meteorological parameters of the construction site; Step S2: Construct an architectural design model, input geographical and environmental parameters into the architectural design model for processing, and obtain the architectural form and layout; Step S3: Obtain the specific roof layout of the building based on the building form layout, install photovoltaic panels and / or small wind turbines in the specific roof layout, and output several layout schemes. Step S4: Conduct preliminary screening of layout schemes based on building constraints; Step S5: Use the Sparrow Search algorithm to optimize the layout scheme after preliminary screening to obtain the optimal layout scheme, and install photovoltaic panels and / or small wind turbines based on the optimal layout scheme. The specific steps of step S2 are as follows: Step S21: Obtain green building design schemes as training data. The green building schemes include the building form and layout used in the design, as well as the corresponding geographical environment parameters and meteorological parameters. Step S22: Obtain actual constructed green buildings as test data. The actual constructed green buildings include the actual building form and layout, as well as the corresponding geographical environment parameters and meteorological parameters collected in real time. Step S23: Construct an architectural design model, train the architectural design model with training data, and after training reaches a preset number of times, test it with test data and calculate the accuracy of the test results. Step S24: Stop training when the accuracy of the test results reaches the preset threshold; otherwise, continue training. Step S25: Input the collected geographical environment parameters and meteorological parameters of the construction site into the trained architectural design model, and obtain the architectural form and layout after processing. The architectural form and layout include the building orientation, facade design, functional zoning, layout of doors and windows, building height and number of floors, and specific roof layout; The specific steps of step S3 are as follows: Step S31: Obtain the installation area from the specific layout of the roof, and randomly fill the center of the installation area with photovoltaic panels or small wind turbines; Step S32: Extend outward from the center of the installation area and randomly fill it with photovoltaic panels or small wind turbines until the installation area can no longer be filled. Step S33: Output the combination of photovoltaic panels and small wind turbines in the installation area as a layout scheme, repeat the above steps, and obtain several layout schemes. The specific steps of step S4 are as follows: Step S41: Analyze the building's electricity demand based on its architectural form and layout; Step S42: Evaluate the power generation capacity in all layout options; Step S43: Eliminate layout schemes where the power generation capacity cannot meet the building's electricity demand; The specific steps of step S5 are as follows: Step S51: Initialize the sparrow population and determine the number of iterations; Step S52: Randomly select a layout scheme and calculate the fitness value of the sparrow based on the lowest cost. Step S53: Select another layout scheme, calculate the fitness value, compare it with the previously calculated fitness value, and retain the layout scheme with the largest fitness value. Step S54: Perform iterative calculations and output the layout scheme with the highest fitness value as the optimal layout scheme; Step S55: Install photovoltaic panels and / or small wind turbines based on the optimal layout scheme.

2. The green building engineering design method according to claim 1, characterized in that, The specific steps of step S1 are as follows: Step S11: Obtain project planning documents, land transfer contracts, or relevant official documents; Step S12: Obtain the specific location of the building construction from the project planning documents, land transfer contract or relevant official documents, and output it as the construction site; Step S13: Input the construction location into the geographic information system to obtain geographic environment parameters; Step S14: Obtain meteorological parameters of the construction site from the meteorological department's database.

3. The green building engineering design method according to claim 2, characterized in that, The geographical environmental parameters include topographic slope and elevation difference, soil type, vegetation type and distribution, and water conditions. The meteorological parameters include average temperature, annual solar altitude angle and azimuth angle, solar radiation intensity, prevailing wind direction and wind speed.

4. The green building engineering design method according to claim 1, characterized in that, In step S32, when filling photovoltaic panels or small wind turbines, the installation space requirements are obtained based on the model of the photovoltaic panels or small wind turbines, and a suitable distance is selected for filling based on the installation space requirements.

5. The green building engineering design method according to claim 1, characterized in that, The number of iterations refers to the number of layout schemes after the initial screening.

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