CN112507439A - Optimization design method for improving building site and building indoor environment performance - Google Patents
Optimization design method for improving building site and building indoor environment performance Download PDFInfo
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Abstract
The invention discloses an optimization design method for improving the performance of a building site and the indoor environment of a building, which comprises the following specific steps: s1: parametric modeling of the target building group; s2: simulating the performance of the field outdoor environment; s3: simulating the indoor environment performance and energy consumption of the building; s4: planning building AI intelligent optimization: and performing intelligent optimization according to indoor and outdoor environment performance and energy consumption simulation to obtain a set with good performance of site planning, outdoor environment and indoor environment of each standard layer. The method comprises the steps of obtaining the orientation and the window-wall ratio of a building when the indoor and outdoor environmental performances of the building are good by simulating the relationship between the orientation and the window-wall ratio of the building and the indoor and outdoor environmental performances of the building, obtaining a building design scheme with good building environmental performance, and realizing planning of a building site according to the obtaining of the orientation of the building when the building environmental performance is good, wherein the orientation and the window-wall ratio of the building when the indoor and outdoor environmental performances of the building are good.
Description
Technical Field
The invention belongs to the technical field of building design, and particularly relates to an optimization design method for improving the performance of a building site and the indoor environment of a building through a computer program.
Background
Due to the rapid development of cities, people pay more and more attention to the quality of work and life, the requirements on the environment performance in places and building rooms are growing day by day, and the technology of green building design of residential areas is brought forward.
For example, in a patent with the patent number "CN 105220896A" and the name "a method for designing green building performance", a method for designing green building performance is disclosed, which comprises the following steps: step 1), an architect completes grass model establishment; step 2), the engineer completes the base analysis of the climate condition, the acoustic environment and the wind environment; step 3), architects and engineers complete the horizontal and vertical sectioning deepening of wind environment, light environment and heat environment; step 4), architects and engineers complete professional integration and green building integration of an evaluation system, energy conservation and non-traditional water source comprehensive management; and 5) finishing scheme finalizing by architects and engineers.
However, with the development of artificial intelligence technology, the traditional designer-based planning architecture design method is gradually replaced by artificial intelligence. A design method for artificial intelligence loading building planning is already available in the market, and for example, a patent with the patent number "CN 109684662A" and the name "a construction method of an intelligent assembly building" discloses an intelligent assembly building construction method. The method comprises the following steps: designing a preliminary model, and carrying out space planning according to field analysis, building modeling, building landscape and traffic flow lines; forming a building full model by using a BIM technology; optimizing model design, putting the building full model into a specific simulation environment, and perfecting the house type, the size and the orientation of the building; deepening model design, splitting the optimization model into single components, and carrying out shape optimization, steel bar configuration and collision detection on the single components according to the splitting of the components; and adjusting each element according to the detection result, further perfecting the relation among the elements, and directly drawing a component deepening detailed drawing by using a BIM (building information modeling) model, wherein the drawing comprises a component size drawing, a pre-buried positioning drawing, a material list table and a constructed H-dimensional view. However, the above patent is also a design method that meets the national and urban sun planning basic requirements as a single target requirement, and does not consider a solution of environment and building performance of a planning site comprehensively.
Disclosure of Invention
In order to solve the above problems, the primary objective of the present invention is to provide an optimal design method for improving the building site and the indoor environmental performance of the building, which comprehensively considers factors such as ventilation, solar radiation, energy consumption and lighting performance of the building units, and designs a design scheme capable of improving the site planning and improving the environmental performance of the building.
The invention also aims to provide an optimization design method for improving the indoor environmental performance of the building site and the building.
Still another object of the present invention is to provide an optimized design method for improving the indoor environmental performance of a building site and a building, which is based on the design requirements of the building site and the building environmental performance, and models a plurality of simulation software (wind, light, heat, etc.) in a centralized manner and considers various environmental factors comprehensively, thereby greatly improving the overall efficiency of building performance design.
In order to achieve the above object, the technical solution of the present invention is as follows.
An optimization design method for improving building site and building indoor environment performance is characterized by comprising the following specific steps:
s1: parametric modeling of a target building group: modeling a target building group, selecting a standard layer of each building of the target building group, acquiring the orientation and the window-wall ratio of each standard layer, and respectively using the orientation and the window-wall ratio as a first variable and a second variable, wherein the site of the target building group changes along with the change of the orientation of each standard layer;
s2: simulating the performance of the field outdoor environment: building outdoor environment systems are established according to the orientation of each standard layer, and outdoor environment performance parameters of each building layer are obtained to be used as outdoor dependent variables;
s3: building indoor environment performance and energy consumption simulation: establishing a building indoor environment and energy consumption system according to the orientation and the window-wall ratio of each standard layer, and acquiring each environment performance parameter and energy consumption parameter in a building as an indoor dependent variable;
s4: planning building AI intelligent optimization: and intelligently optimizing according to the first variable, the second variable, the outdoor dependent variable and the indoor dependent variable to obtain a set with good performance of site planning, outdoor environment and indoor environment of each standard layer. The invention obtains the orientation and the window-wall ratio of the building when the indoor and outdoor environmental performance of the building is good by simulating the relationship between the orientation and the window-wall ratio of the building and the indoor and outdoor environmental performance of the building, thereby obtaining the design scheme (the orientation and the window-wall ratio) of the building with good environmental performance of the building.
Further, in S3, a sunshine duration digital simulation system is established according to the orientation and window-wall ratio of each standard floor, the sunshine duration in the winter solstice is obtained, a forced sunshine planning condition of the location of the target building group is used as a first constraint condition, and when the sunshine duration in the winter solstice does not satisfy the first constraint condition, the first variable and the second variable are readjusted. The winter solstice is the judging date for judging whether each building in the residential area obtains enough sunshine all the year round, and the countries and all the regions basically adopt the winter solstice as the standard for judging whether the buildings meet the sunshine requirement or not. Because we are in northern hemisphere, in winter solstice day, the angle of sunlight and each place of our northern hemisphere is minimum, also is the date that it is the hardest to obtain sunshine, if this date, sunshine satisfies the requirement, then other times of the whole year also can satisfy the sunshine requirement naturally.
Further, in S3, a building radiation digital analog system is established according to the orientation and the window-wall ratio of each standard layer, a building radiation value in winter solstice is obtained, a minimum value of the building radiation value is set, the minimum value is used as a second constraint condition, and when the building radiation value in winter solstice does not satisfy the second constraint condition, the first variable and the second variable are readjusted.
The setting of the first constraint condition and the second constraint condition limits the conditions met by the building design, and after the building design meets the first constraint condition and the second constraint condition, the building has basic illumination requirements.
Further, in S2, the outdoor dependent variable includes a first dependent variable, the building outdoor environment system includes a site solar radiation simulation system, and the site solar radiation simulation system is used to obtain an average radiation value of the target building group, and the average radiation value is used as the first dependent variable.
In S2, the outdoor dependent variable includes a second dependent variable, and the windward area ratio of the target building group is obtained from the initial orientation of each standard storey of the target building group, and is used as the second dependent variable.
Further, in S3, the indoor dependent variable includes a third dependent variable and a fourth dependent variable, the building indoor environment and energy consumption system includes an indoor light environment digital simulation system and a building energy consumption digital simulation system, and the indoor light environment digital simulation system is used to obtain an indoor average illuminance value as the third dependent variable; and acquiring the annual average energy consumption value of the building by using the digital building energy consumption analog system as a fourth dependent variable.
The outdoor first dependent variable, the outdoor second dependent variable, the indoor third dependent variable and the indoor fourth dependent variable are used as parameters of indoor and outdoor environmental performance and respectively represent outdoor solar radiation, ventilation, indoor lighting and energy consumption of single buildings, after an intelligent optimization process is carried out, the design (the design of the building orientation and the window-wall ratio) of the building meeting the performance of the outdoor solar radiation, the ventilation, the indoor lighting and the energy consumption of the single buildings is obtained, and therefore the design of the building meeting the indoor and outdoor annular performance of the building can be obtained. And the design of the orientation of the building represents the planning of the site of the building.
Further, in the intelligent optimization process of S4, a third dependent variable is transformed, and the specific method of the transformation is as follows: the third dependent variable is divided by 1000. In the intelligent optimization process, in order to make the first dependent variable, the second dependent variable, the third dependent variable and the fourth dependent variable consistent with the trend of the intelligent optimization direction (the smaller the more the better), the third dependent variable is divided by 1000.
Further, the intelligent optimization in S4 includes connecting the first variable, the second variable, the outdoor dependent variable, and the indoor dependent variable to Octopus in the Rhnio + Grasshopper, and setting a population number and a population variation index of the Octopus. The first variable and the second variable are connected with the input end of the Octopus, and the first dependent variable, the second dependent variable, the third dependent variable and the fourth dependent variable are connected with the output end of the Octopus.
Furthermore, the method also comprises an intelligent decision module, and a design scheme with comprehensive better site and building performance is screened out by utilizing the intelligent decision module. In an intelligent decision module, the output end of Octopus is connected with Wallace, and a planning scheme with comprehensively optimal site and building performance is screened out through AI intelligent decision.
Further, the field solar radiation simulation system obtains an average radiation value in summer. Selecting winter solstice day as sunshine, considering indoor, because the regulation of sunshine is to use sunshine time of a building window as an evaluation index in national and local regulations, and the sunshine of the building window in winter meets requirements, the area occupation ratio meeting the winter sunshine requirements in a corresponding field is naturally increased (because the obtained sunshine of the building is related to building shielding); secondly, the outdoor thermal environment is based on summer simulation, mainly because summer is an important season influencing the thermal comfort of the outdoor site, if the thermal environment of the site is improved, people naturally prefer to move in the site without staying indoors, so that the use of indoor air conditioners can be reduced, and further electricity can be saved.
The invention obtains the orientation and the window-wall ratio of the building when the indoor and outdoor environmental performance of the building is good by simulating the relationship between the orientation and the window-wall ratio of the building and the indoor and outdoor environmental performance of the building, thereby obtaining the design scheme (the orientation and the window-wall ratio) of the building with good environmental performance.
According to the invention, through a plurality of environment performance optimization targets of the building indoor light environment and the building energy consumption, and by using an artificial intelligence algorithm to carry out an optimization design method in the scheme early stage, the integrated simulation of multiple environment performances such as building wind, light, heat, energy consumption and the like is simplified, and through an artificial intelligence technology, after the comprehensive optimization decision of the field and the building indoor environment performance, a solution for integrating the field wind environment and the heat environment, the indoor light environment and the building energy consumption is intelligently generated.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a partially enlarged view of a portion a in fig. 1.
Fig. 3 is a partially enlarged view of a portion B in fig. 1.
Fig. 4 is a graph of the comparison of the indoor average illuminance before and after the optimization of the present invention.
Fig. 5 is a graph of average radiation contrast of a building site before and after optimization in accordance with the present invention.
FIG. 6 is a graph comparing average energy consumption of building groups before and after optimization according to the present invention.
FIG. 7 is a graph comparing average wind speeds of a building site before and after optimization according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1 to 7, an optimized design method for improving the performance of a building site and a building indoor environment according to the present invention includes the following specific steps:
s1: parametric modeling of a target building group: modeling a target building group, selecting a standard layer of each building of the target building group, acquiring the orientation and the window-wall ratio of each standard layer, and respectively using the orientation and the window-wall ratio as a first variable and a second variable, wherein the site of the target building group changes along with the change of the orientation of each standard layer;
in this embodiment, a target building group and a surrounding building group plane are imported into Rhnio, and modeling is performed according to the actual building height using the imported building group plane, thereby generating a 3D model and completing modeling of the target building group.
The standard floors of the buildings are used as representatives of the buildings, wherein the standard floors select the bottom floor with the worst performance in the buildings to reflect the overall performance of the buildings. The orientation ranges from-180 to 180 degrees.
The building is divided into layers such as a roof, an outer wall, an outer window, a floor slab and the like, and the window-wall ratio of each standard layer is obtained according to the layers.
S2: simulating the performance of the field outdoor environment: building outdoor environment systems are established according to the orientation of each standard layer, and outdoor environment performance parameters of each building layer are obtained to be used as outdoor dependent variables;
s3: building indoor environment performance and energy consumption simulation: establishing a building indoor environment and energy consumption system according to the orientation and the window-wall ratio of each standard layer, and acquiring each environment performance parameter and energy consumption parameter in a building as an indoor dependent variable;
s4: planning building AI intelligent optimization: and intelligently optimizing according to the first variable, the second variable, the outdoor dependent variable and the indoor dependent variable to obtain a set with good performance of site planning, outdoor environment and indoor environment of each standard layer. The invention obtains the orientation and the window-wall ratio of the building when the indoor and outdoor environmental performance of the building is good by simulating the relationship between the orientation and the window-wall ratio of the building and the indoor and outdoor environmental performance of the building, thereby obtaining the design scheme (the orientation and the window-wall ratio) of the building with good environmental performance of the building.
In S3, a sunshine duration digital simulation system is established according to the orientation and window-wall ratio of each standard floor, the sunshine duration in winter solstice is obtained, a forced sunshine planning condition of the location of the target building group is used as a first constraint condition, and when the sunshine duration in winter solstice does not satisfy the first constraint condition, the first variable and the second variable are readjusted. The winter solstice is the judging date for judging whether each building in the residential area obtains enough sunshine all the year round, and the countries and all the regions basically adopt the winter solstice as the standard for judging whether the buildings meet the sunshine requirement or not. Because we are in northern hemisphere, in winter solstice day, the angle of sunlight and each place of our northern hemisphere is minimum, also is the date that it is the hardest to obtain sunshine, if this date, sunshine satisfies the requirement, then other times of the whole year also can satisfy the sunshine requirement naturally.
In S3, a building radiation digital analog system is established according to the orientation and the window-wall ratio of each standard layer, a building radiation value in winter solstice is obtained, a minimum value of the building radiation value is set, the minimum value is used as a second constraint condition, and when the building radiation value in winter solstice does not satisfy the second constraint condition, the first variable and the second variable are readjusted. The minimum value of the building radiation value is the maximum 1-hour radiation quantity of 11: 30-12: 30 at noon of the winter solstice day of the building location.
The setting of the first constraint condition and the second constraint condition limits the conditions met by the building design, and after the building design meets the first constraint condition and the second constraint condition, the building has basic illumination requirements. And when the sunshine hours in the winter solstice day do not meet the first constraint condition or the building radiation value in the winter solstice day does not meet the second constraint condition, adjusting the orientation and the window-wall ratio of each standard layer. So that the requirements of the first constraint condition and the second constraint condition are met respectively.
In S2, the outdoor dependent variable includes a first dependent variable, the building outdoor environment system includes a site solar radiation simulation system, and the site solar radiation simulation system is used to obtain an average radiation value of the target building group, and the average radiation value is used as the first dependent variable.
In S2, the outdoor dependent variable includes a second dependent variable, and the windward area ratio of the target building group is obtained from the initial orientation of each standard storey of the target building group, and is used as the second dependent variable. The frontal area ratio is the ratio of the frontal area of the main air guide of the current building group to the maximum possible frontal area.
In S3, the indoor dependent variable includes a third dependent variable and a fourth dependent variable, the building indoor environment and energy consumption system includes an indoor light environment digital simulation system and a building energy consumption digital simulation system, and the indoor light environment digital simulation system is used to obtain an indoor average illuminance value as the third dependent variable; and acquiring the annual average energy consumption value of the building by using the digital building energy consumption analog system as a fourth dependent variable.
The outdoor first dependent variable, the outdoor second dependent variable, the indoor third dependent variable and the indoor fourth dependent variable are used as parameters of indoor and outdoor environmental performance and respectively represent outdoor solar radiation, ventilation, indoor lighting and energy consumption of single buildings, after an intelligent optimization process is carried out, the design (the design of the building orientation and the window-wall ratio) of the building meeting the performance of the outdoor solar radiation, the ventilation, the indoor lighting and the energy consumption of the single buildings is obtained, and therefore the design of the building meeting the indoor and outdoor annular performance of the building can be obtained. And the design of the orientation of the building represents the planning of the site of the building.
In the intelligent optimization process of S4, the third dependent variable is transformed, and the specific method of the transformation is as follows: the third dependent variable is divided by 1000. In the intelligent optimization process, in order to make the first dependent variable, the second dependent variable, the third dependent variable and the fourth dependent variable consistent with the trend of the intelligent optimization direction (the smaller the more the better), the third dependent variable is divided by 1000.
The intelligent optimization in S4 includes connecting the first variable, the second variable, the outdoor dependent variable, and the indoor dependent variable to Octopus in the Rhnio + Grasshopper, and setting a population number and a population variation index of the Octopus. The first variable and the second variable are connected with the input end of the Octopus, and the first dependent variable, the second dependent variable, the third dependent variable and the fourth dependent variable are connected with the output end of the Octopus.
In this embodiment, in the intelligent optimization process, Octopus in Rhnio + Grasshopper is taken as a core, a genetic evolution algorithm SPEA2 (standard change strength pareto convergence) is taken as a core algorithm, a variation algorithm Polynomial (Polynomial variation method) is loaded, and the first variable and the second variable are connected to an input end of Octopus.
In this embodiment, in order to ensure that the trend of the variation of the environmental performance in the value range coincides with the trend of "smaller is better" of the optimizing direction of Octopus, the first dependent variable R is adjusted to R '═ R × 1, the second dependent variable V is adjusted to V' ═ V × 1, the third dependent variable I is adjusted to I '═ 1000/I, and the fourth dependent variable E is adjusted to E' ═ E1; and the adjusted first dependent variable R ', second dependent variable V', third dependent variable I 'and fourth dependent variable E' are transmitted to the output end of Octopus.
In this embodiment, the population number in Octopus is set to 100 generations, the population variation index is 0.2, and Octopus is operated and smart optimization is performed.
The method further comprises an intelligent decision module, and the intelligent decision module is utilized to screen out a design scheme with comprehensive and excellent site and building performance. In an intelligent decision module, the output end of Octopus is connected with Wallace, and a planning scheme with comprehensively optimal site and building performance is screened out through AI intelligent decision.
The field solar radiation simulation system obtains the average radiation value in summer. Selecting winter solstice day as sunshine, considering indoor, because the regulation of sunshine is to use sunshine time of a building window as an evaluation index in national and local regulations, and the sunshine of the building window in winter meets requirements, the area occupation ratio meeting the winter sunshine requirements in a corresponding field is naturally increased (because the obtained sunshine of the building is related to building shielding); secondly, the outdoor thermal environment is based on summer simulation, mainly because summer is an important season influencing the thermal comfort of the outdoor site, if the thermal environment of the site is improved, people naturally prefer to move in the site without staying indoors, so that the use of indoor air conditioners can be reduced, and further electricity can be saved.
Example (b):
1) selecting a resident region building group in the Shenzhen region, introducing 6 buildings and peripheral building planes in the resident region into the Rhnio, and stretching to establish a 3D model;
2) calling Grasshopper to define the initial orientation of each building as a positive south orientation of 0 degrees, defining the orientation of each building to change from-180 degrees to 180 degrees, and taking the orientation of each building as a variable 1 for optimizing the performance of the residential area;
3) picking up each building group in the residential area, equally dividing each building into 32 layers, and calling a bottom standard layer with the worst performance of each building as an object reflecting the overall performance of the site and each building;
4) calling Grasshopper and Honeybee components for programming, giving the initial window-wall ratio W of each building group to be 0.5, and picking up an outer wall, an outer window, a floor slab and a roof layer of a bottom standard layer;
5) picking up the outer window layer in the step 4), calling the Ladybug suite, establishing a sunshine duration digital simulation system for simulation, obtaining the direct sunshine duration change of each bottom layer outer window in the winter solstice to be (1.1-6.5 h), and taking 1 hour of the winter solstice day required by the Shenzhen region residential building as a constraint condition 1;
6) calling a Ladybug suite, establishing a building radiation digital simulation system for simulation, selecting the average solar radiation intensity R0 of a site without building shielding in the site at 1 hour of 11: 30-12: 30 at noon as 1.34 kwh/square meter, and taking R0 as a constraint condition 2 of the building radiation simulation system;
7) picking up the outer window layer in the step 4), connecting the outer window layer with the building radiation digital simulation system in the step 6), and simulating to obtain that the average radiation intensity variation range of each outer window in winter solstice days is (0.62-1.98 kwh/square meter);
8) the minimum value of the range is 0.62kwh per square meter and is less than 1.34kwh per square meter under the constraint condition of 2; therefore, the initial orientation of each building in the step 2) is adjusted to be 30 degrees, and the steps 5) and 6) are repeated, so that the change of the direct irradiation and sunshine hours in winter solstice days is (1.3-5.4 h), the change range of the average radiation intensity in winter solstice days is (1.36-1.74 kwh/square meter), and the requirements of constraint condition 1 and constraint condition 2 are met;
9) calling a Honeybee suite, picking up each layer of each building bottom layer in 4), establishing an indoor light environment digital simulation system and a Honeybee building energy consumption digital simulation system, and operating the two systems to obtain an initial indoor average illuminance value I of 350.62lux and an initial building energy consumption value E of 96.78 kwh/square meter;
10) calling a Grasshopper assembly, picking up each building model in the step 1), establishing a residential building group windward area ratio calculation formula, and obtaining that the windward area ratio V of the existing building facing downwards is 0.43;
11) calling the Ladybug suite to establish a site radiation environment digital simulation system to obtain the summer accumulated solar radiation intensity R in the building group site as 3521 kwh;
12) taking the building orientation in 2) and the window-wall ratio in 4) as variables; taking the average illumination value I and the building energy consumption E in the 9) as a dependent variable 1 and a dependent variable 2 for reflecting the building performance, and taking the windward area ratio V and the solar radiation intensity R of the 10) and the 11) as a dependent variable 3 and a dependent variable 4 for reflecting the performance of the building;
13) respectively connecting the variable and the dependent variable in 12) to a variable end and a dependent variable end in Octopus;
14) the system is operated, and through 1 day of intelligent decision optimization, 45 solutions of the pareto scheme with comprehensively optimal field wind environment, field radiation environment, indoor light environment and building energy consumption are decided;
15) the method comprises the steps of connecting a pareto solution set of Octopus to a Wallacie data processing end, intelligently screening a scheme of comprehensively ranking 1 st indoor light environment, heat environment and building energy consumption, wherein the optimal windward area ratio V of a residential area is 0.32, the optimal field radiation intensity in summer is 2765kwh, the optimal indoor average illumination value is 435lux, the optimal building energy consumption is 81.67 kwh/square meter, the orientation of each corresponding building is 27 degrees, 15 degrees, -13 degrees, 32 degrees, 25 degrees, -9 degrees, and the corresponding window-wall ratio is 0.27.
The invention provides a parameterization design method for site environment and building indoor environment, which provides a set of optimization targets for site wind environment and thermal environment, building indoor luminous environment and building energy consumption, and utilizes an artificial intelligence algorithm to carry out optimization design at the front stage of a scheme, so that the integration simulation of multiple environment performances such as building wind, light, heat, energy consumption and the like is simplified, and a solution for intelligently generating the optimal comprehensive site wind environment and thermal environment, indoor luminous environment and building energy consumption is intelligently generated after comprehensive optimization decision of site and building indoor environment performances is made through an artificial intelligence technology.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An optimization design method for improving building site and building indoor environment performance is characterized by comprising the following specific steps:
s1: parametric modeling of a target building group: modeling a target building group, selecting a standard layer of each building of the target building group, acquiring the orientation and the window-wall ratio of each standard layer, and respectively using the orientation and the window-wall ratio as a first variable and a second variable, wherein the site of the target building group changes along with the change of the orientation of each standard layer;
s2: simulating the performance of the field outdoor environment: building outdoor environment systems are established according to the orientation of each standard layer, and outdoor environment performance parameters of each building layer are obtained to be used as outdoor dependent variables;
s3: building indoor environment performance and energy consumption simulation: establishing a building indoor environment and energy consumption system according to the orientation and the window-wall ratio of each standard layer, and acquiring each environment performance parameter and energy consumption parameter in a building as an indoor dependent variable;
s4: planning building AI intelligent optimization: and intelligently optimizing according to the first variable, the second variable, the outdoor dependent variable and the indoor dependent variable to obtain a set with good performance of site planning, outdoor environment and indoor environment of each standard layer.
2. The optimal design method for improving the performance of the building site and the indoor environment of the building as claimed in claim 1, wherein in S3, a sunshine duration digital simulation system is established according to the orientation and the window-wall ratio of each standard floor, the sunshine duration in winter solstice is obtained, the forced condition of sunshine planning at the location of the target building group is used as the first constraint condition, and when the sunshine duration in winter solstice does not satisfy the first constraint condition, the first variable and the second variable are readjusted.
3. The optimal design method for improving the indoor environmental performance of buildings and construction sites as claimed in claim 1, wherein in S3, a building radiation digital simulation system is established according to the orientation and window-wall ratio of each standard floor, the building radiation value in winter solstice is obtained, the minimum value of the building radiation value is set, the minimum value is used as the second constraint condition, and when the building radiation value in winter solstice does not satisfy the second constraint condition, the first variable and the second variable are readjusted.
4. The method of claim 1, wherein in step S2, the dependent variable outside the building comprises a first dependent variable, the building outdoor environment system comprises a site solar radiation simulation system, and the site solar radiation simulation system is used to obtain an average radiation value of the target building group, and the average radiation value is used as the first dependent variable.
5. The optimal design method for improving the indoor environment performance of buildings and construction sites as claimed in claim 1, wherein in S2, the dependent variable outside the building comprises a second dependent variable, and the windward area ratio of the target building group is obtained according to the initial orientation of each standard storey of the target building group and is used as the second dependent variable.
6. The optimal design method for improving the performance of the building site and the building indoor environment according to claim 1, wherein in S3, the dependent variable of the indoor environment includes a third dependent variable and a fourth dependent variable, the building indoor environment and energy consumption system includes an indoor light environment digital simulation system and a building energy consumption digital simulation system, and the indoor light environment digital simulation system is used to obtain an indoor average illuminance value as the third dependent variable; and acquiring the annual average energy consumption value of the building by using the digital building energy consumption analog system as a fourth dependent variable.
7. The optimization design method for improving the performance of the building site and the indoor environment of the building as claimed in claim 6, wherein in the intelligent optimization process of S4, a third dependent variable is transformed by: the third dependent variable is divided by 1000.
8. The optimization design method for improving the performance of the building site and the indoor environment of the building according to claim 1, wherein the intelligent optimization in S4 comprises connecting the first variable, the second variable, the outdoor dependent variable and the indoor dependent variable to Octopus in Rhnio + Grasshopper, and setting the population number and the population variation index of Octopus.
9. The method as claimed in claim 1, further comprising an intelligent decision module for selecting a design solution with better integration of site and building indoor environment.
10. The optimization design method for improving the performance of the building site and the indoor environment of the building as claimed in claim 4, wherein the site solar radiation simulation system obtains the average radiation value in summer.
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