A temperature adjustment method and system based on commercial pedestrian street thermal comfort

Abstract

The application discloses a temperature adjustment method and system based on commercial pedestrian street thermal comfort, and the method comprises the following steps: statistically analyzing the morphological characteristics of commercial pedestrian streets in a target area where a target commercial pedestrian street is located to obtain a plurality of typical models of commercial pedestrian streets in the target area; collecting street block building data, 3D space data and meteorological data of the target commercial pedestrian street; clustering the street block building data to obtain an optimal model from the plurality of typical models of commercial pedestrian streets; simulating the thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data; adjusting the geometric shape of the target commercial pedestrian street based on the optimal model, and adjusting the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics. The application systematically analyzes the comprehensive influence of the geometric shape and the thermal environment characteristics of the commercial pedestrian street block on the thermal comfort of the commercial pedestrian street, and effectively improves the thermal comfort of the commercial pedestrian street.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of urban environment planning and climate adaptive design, and particularly relates to a temperature adjustment method and system based on thermal comfort of commercial pedestrian street, a terminal and a computer readable storage medium. BACKGROUND

[0002] The technical means commonly used in the optimization of thermal environment in architecture and urban planning include thermal environment simulation, meteorological data analysis and the influence research of building geometry. These researches often focus on how to improve the thermal comfort of pedestrian street through greening, shading facilities and ventilation design, and reduce the temperature of pedestrian street by using reflective materials and installing spray cooling systems.

[0003] The climate adaptive design method is mainly applied in architecture and urban planning, focusing on designing buildings and space layouts that adapt to specific climate conditions. Common design strategies include using energy-saving materials, optimizing building orientation and designing effective natural ventilation systems.

[0004] However, the climate adaptive design method is mainly applied in architecture and urban planning, focusing on designing buildings and space layouts that adapt to specific climate conditions, and the thermal comfort problem of busy commercial areas is often ignored. The existing thermal environment optimization of commercial pedestrian street mainly focuses on the influence analysis of a single factor, such as only focusing on the effect of green belts or shading facilities, lacks systematic research on the geometry of pedestrian street, and fails to systematically optimize the geometry of pedestrian street and design combined with local climate adaptability.

[0005] Therefore, the prior art still needs to be improved and developed. SUMMARY

[0006] The main purpose of the present application is to provide a temperature adjustment method and system based on thermal comfort of commercial pedestrian street, a terminal and a computer readable storage medium, which aims to solve the problem of lack of comprehensive consideration of the geometry of pedestrian street and climate adaptability in the existing thermal environment optimization scheme of commercial pedestrian street, resulting in poor thermal comfort of pedestrian street.

[0007] To achieve the above purpose, the present application provides a temperature adjustment method based on thermal comfort of commercial pedestrian street, which comprises the following steps:

[0008] Statistically analyzing the morphological characteristics of commercial pedestrian streets in the target area where the target commercial pedestrian street is located, to obtain a plurality of typical models of commercial pedestrian streets in the target area;

[0009] Collecting street building data, 3D space data and meteorological data of the target commercial pedestrian street;

[0010] performing clustering on the street building data to obtain an optimal model from a plurality of the commercial pedestrian street typical models;

[0011] simulate thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data;

[0012] adjust the geometric shape of the target commercial pedestrian street based on the optimal model, and adjust the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics.

[0013] Optionally, the temperature adjustment method based on thermal comfort of a commercial pedestrian street, wherein the street building data, the 3D space data and the meteorological data are collected by a sensor network.

[0014] The street building data includes street width, street length, building floor number, building open span, building depth, courtyard open span and courtyard depth.

[0015] The 3D space data includes geometric shape, building layout, street orientation and vegetation distribution.

[0016] The meteorological data includes temperature, humidity, wind speed and solar radiation.

[0017] Optionally, the temperature adjustment method based on thermal comfort of a commercial pedestrian street, wherein the performing clustering on the street building data to obtain an optimal model from a plurality of the commercial pedestrian street typical models specifically includes:

[0018] respectively calculate the mean and standard deviation of each parameter in the street building data, and perform standardization processing on each parameter in the street building data according to the mean and the standard deviation to obtain standard street building data;

[0019] determine the optimal cluster number in the K-means clustering algorithm through the elbow rule, and perform clustering on the standard street building data according to the optimal cluster number through the K-means clustering algorithm to obtain an optimal model from a plurality of the commercial pedestrian street typical models.

[0020] Optionally, the temperature adjustment method based on thermal comfort of a commercial pedestrian street, wherein the simulating thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data specifically includes:

[0021] input the 3D space data and the meteorological data into ENVI-met for simulation to generate spatial distribution and temporal distribution of thermal environment;

[0022] The thermal environment of the space distribution and the time distribution is evaluated to obtain the thermal environment characteristics of the target commercial pedestrian street.

[0023] Optionally, the temperature adjustment method based on the thermal comfort of the commercial pedestrian street, wherein the geometric form comprises building layout, street orientation and 3D form adjustment.

[0024] The cooling equipment comprises a green plant covering system, a spray cooling system and a sunshade system.

[0025] Optionally, the temperature adjustment method based on the thermal comfort of the commercial pedestrian street, wherein the adjustment of the geometric form of the target commercial pedestrian street according to the optimal model comprises:

[0026] The optimal building layout, the optimal street orientation and the optimal 3D form of the target commercial pedestrian street are obtained according to the optimal model.

[0027] The building arrangement mode, the building density and the building height of the target commercial pedestrian street are adjusted according to the optimal building layout.

[0028] The street orientation of the target commercial pedestrian street is adjusted according to the optimal street orientation to reduce the accumulation of solar radiation heat.

[0029] The building volume form coefficient and the surface area ratio of the target commercial pedestrian street are adjusted according to the optimal 3D form.

[0030] Optionally, the temperature adjustment method based on the thermal comfort of the commercial pedestrian street, wherein the adjustment of the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics comprises:

[0031] The temperature of each region in the target commercial pedestrian street is determined according to the thermal environment characteristics, and a target region with temperature exceeding a preset threshold is obtained.

[0032] The green plant coverage of the green plant covering system in the target region is increased, and the sunshade facility of the sunshade system in the target region is increased.

[0033] The spray cooling system is arranged in the target region, and the air humidity of the target region is increased by regularly spraying small water mist.

[0034] In addition, to achieve the above-mentioned purpose, the application further provides a temperature adjustment system based on the thermal comfort of the commercial pedestrian street, wherein the temperature adjustment system based on the thermal comfort of the commercial pedestrian street comprises:

[0035] A typical model construction module is configured to statistically analyze morphological characteristics of commercial pedestrian streets in a target region where a target commercial pedestrian street is located, and obtain a plurality of typical models of commercial pedestrian streets in the target region;

[0036] A data acquisition module is configured to acquire block building data, 3D space data and meteorological data of the target commercial pedestrian street;

[0037] An optimal model acquisition module is configured to cluster the block building data, and obtain an optimal model from the plurality of typical models of commercial pedestrian streets;

[0038] A thermal environment feature generation module is configured to simulate thermal environment features of the target commercial pedestrian street according to the 3D space data and the meteorological data;

[0039] A comfort optimization module is configured to adjust a geometric morphology of the target commercial pedestrian street based on the optimal model, and adjust a cooling device of the target commercial pedestrian street according to the thermal environment features.

[0040] In addition, to achieve the above object, the present application further provides a terminal, wherein the terminal comprises a memory, a processor, and a commercial pedestrian street thermal comfort based temperature adjustment program stored in the memory and executable on the processor, and the commercial pedestrian street thermal comfort based temperature adjustment program implements the steps of the commercial pedestrian street thermal comfort based temperature adjustment method when executed by the processor.

[0041] In addition, to achieve the above object, the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a commercial pedestrian street thermal comfort based temperature adjustment program, and the commercial pedestrian street thermal comfort based temperature adjustment program implements the steps of the commercial pedestrian street thermal comfort based temperature adjustment method when executed by a processor.

[0042] In the present application, the morphological characteristics of commercial pedestrian streets in a target region where a target commercial pedestrian street is located are statistically analyzed, and a plurality of typical models of commercial pedestrian streets in the target region are obtained; block building data, 3D space data and meteorological data of the target commercial pedestrian street are acquired; the block building data is clustered, and an optimal model is obtained from the plurality of typical models of commercial pedestrian streets; thermal environment features of the target commercial pedestrian street are simulated according to the 3D space data and the meteorological data; and a geometric morphology of the target commercial pedestrian street is adjusted based on the optimal model, and a cooling device of the target commercial pedestrian street is adjusted according to the thermal environment features. The present application systematically analyzes the comprehensive influence of the geometric morphology and thermal environment features of a commercial pedestrian street block on the thermal comfort of a commercial pedestrian street, and effectively improves the thermal comfort of a commercial pedestrian street. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 is a flow chart of a preferred embodiment of the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0044] Figure 2 is a plan view of 32 typical commercial pedestrian street models in the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0045] Figure 3 is a combined schematic view of 32 typical models in the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0046] Figure 4 is a positive and negative space comparison view of A city and B city in the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0047] Figure 5 is a satellite image schematic view of 22 sample points in the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0048] Figure 6 is a schematic view of the best model of commercial pedestrian street in the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0049] Figure 7 is a schematic view of the geometric shape constraint of the target commercial pedestrian street in the temperature adjustment method based on thermal comfort of commercial pedestrian street of the present application;

[0050] Figure 8 is a structure view of a preferred embodiment of the temperature adjustment system based on thermal comfort of commercial pedestrian street of the present application;

[0051] Figure 9 is a running environment schematic view of a preferred embodiment of the terminal of the present application. DETAILED DESCRIPTION

[0052] The present application provides a temperature adjustment method based on thermal comfort of commercial pedestrian street and related equipment. In order to make the purpose, technical scheme and effect of the present application more clear and explicit, the present application is further described in detail below with reference to the drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0053] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as such herein.

[0054] In addition, if the embodiments of the present application involve descriptions such as "first", "second", etc., the descriptions of "first", "second", etc. are only for descriptive purposes, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implying the number of the indicated technical features. Therefore, the features defined as "first" and "second" can be explicitly or implicitly included at least one of the features. In addition, the technical solutions of various embodiments can be combined with each other, but must be based on the realization of ordinary skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, nor within the scope of protection required by the present application.

[0055] The temperature adjustment method based on the thermal comfort of the commercial pedestrian street according to the preferred embodiment of the present application, as shown in Figure 1 and Figure 2 The temperature adjustment method based on the thermal comfort of the commercial pedestrian street includes the following steps:

[0056] Step S10, statistical analysis is performed on the morphological characteristics of the commercial pedestrian street in the target region where the target commercial pedestrian street is located, to obtain a plurality of typical models of the commercial pedestrian street in the target region.

[0057] In this embodiment, the commercial pedestrian street area of a certain city (the target region) in the warm temperate semi-humid climate of the northwest target region is taken as an example to construct a plurality of typical models of the commercial pedestrian street in the target region; the typical model of the commercial pedestrian street refers to a representative model for analyzing and simulating the influence of the urban street form on the local climate (microclimate). These models abstract and simplify the typical characteristics of the urban street in terms of spatial layout, building form, street width, height, green coverage, etc., and analyze or predict the change characteristics of the microclimate through interaction with climate elements.

[0058] Specifically, under the background of the unique chessboard urban form layout of the target region, three parts of work are done to make the model better reflect the urban geometric form characteristics: sample clustering survey, clustering index selection, and clustering method application. As shown in Figure 2 Based on the statistical analysis of the morphological characteristics of the commercial pedestrian street in the target region, and based on the built information, 32 typical models conforming to the morphological characteristics of the commercial pedestrian street in the target region are established in this study.

[0059] The building layout form refers to different arrangement and combination modes of building monomers and building groups, which can hinder or promote air flow in the region, and directly affect the solar radiation received by the plot and the ventilation environment, and further affect the regional thermal environment. According to the common building layout form of the commercial pedestrian street in the target area, the present application designs four different building layout forms, which are plate type, strip type, courtyard type and single-family house type layout. In order to verify the climate performance of all urban street canyon categories, the above parameters are combined to cover all possibilities, so as to obtain 32 canyon types, as shown in Figure 3

[0060] The results obtained by K-means clustering analysis of the sample street width, length, building bay, building depth, building height, courtyard bay and courtyard depth are shown in Table 1. In the clustering process of building bay, depth and courtyard bay depth, two clusters can be obtained in two clustering processes, which reflect the horizontal and vertical layout of the building base shape. Therefore, the combination of various elements with typical configuration modes forms 32 typical commercial pedestrian street scenes Figure 3 From the clustering results, it can be seen that the difference between the horizontal and vertical layout of the building base shape in the large-scale street is not obvious, and it does not have the characteristics of courtyard layout, so the two forms are not considered in the large-scale clustering results. In order to compare and analyze, 32 scenes are divided into two groups according to the street orientation, and are named as case A (south-north orientation) and case B (east-west orientation) group according to the different street orientation; according to the different street length-width ratio scale, it is divided into C (5m*262m) group and D (11m-566m) group; according to the different building base shape, it is divided into a (12m*17m) (vertical) group and b (15m*10m) (horizontal) group. For example, Case A-C-a-1 represents the south-north orientation of the small-scale strip layout, and the building base shape is vertical layout.

[0061] Table 1: Variable clustering results

[0062] Variable name Clustering result (small scale) Clustering result (large scale) Street length and width 5m*262m 11m*566m Building bay, depth, number of floors 12m*17m*3f / 15m*10m*3f 28m*54m*3F Courtyard bay, depth 8m*11m / 14m*9m /

[0063] It can be understood that in the earliest research, the most direct field measurement method is mostly used for the quantification of urban geometry. The present application divides the geometry into 2D index and 3D index two parts to quantitatively process the form in the site, so as to effectively extract the real environment of different form characteristics and uniformity, and improve the accuracy of subsequent strategy formulation.

[0064] Step S20, collecting the block building data, 3D space data and meteorological data of the target commercial pedestrian street.

[0065] ​In this embodiment, a north-south oriented commercial pedestrian street within the target area is selected for study. The street has an area of ​​5,000 square meters, a street width of 10 meters, and buildings of varying heights. The street's architectural data, 3D spatial data, and meteorological data are all collected by a sensor network. The street's architectural data includes street width, street length, number of building floors, building span, building depth, courtyard span, and courtyard depth. The 3D spatial data includes geometric shape, building layout, street orientation, and vegetation distribution. The meteorological data includes temperature, humidity, wind speed, and solar radiation.

[0066] Step S30: Perform clustering processing on the street building data to obtain the best model from multiple typical commercial pedestrian street models.

[0067] In this embodiment, the geometric morphology information of multiple commercial pedestrian streets in the target area was investigated, and 32 typical commercial pedestrian street models were constructed to represent the target area. Then, thermal environment analysis was used to determine which of the 32 typical commercial pedestrian street models was most suitable for the target commercial pedestrian street.

[0068] Specifically, the mean and standard deviation of each parameter in the street building data are calculated respectively, and the parameters in the street building data are standardized according to the mean and standard deviation to obtain standard street building data.

[0069] It is understandable that, such as Figure 4 As shown in (a1), (a2), (b1), and (b2), (a1) and (a2) represent the positive and negative spaces of city A, respectively, and (b1) and (b2) represent the positive and negative spaces of city B, respectively. Each city has unique macroscopic, mesoscopic, and microscopic geometric forms. East-West cities, historical-contemporary cities, and mountain-plain cities all exhibit significant spatial differences due to their morphological backgrounds. From the positive and negative space diagrams of cities B and A, one can directly perceive the differences in the composition of architectural and street spaces. The street space ratio in city B tends to be balanced, with a street-to-building ratio of approximately 4:6. The space is distributed along plots that are longer east-west and shorter north-south, with extremely high accessibility and little difference in road hierarchy among plots. The street space ratio in city A is significantly different, with a street-to-building ratio of approximately 2:8. The buildings are dense, making it difficult to distinguish the relationship between streets and buildings from the black-and-white inverted diagram. It follows the grid-like layout of ancient streets. At the same time, the axis of the urban canyon expresses the direction of spatial extension, with the main direction (i.e., NS, EW) being dominant in the unique chessboard-like urban morphological layout of city A. In order to make the samples better reflect the geometric features of the city, this invention uses the statistical method of clustering to make the samples better reflect the typical form of a city.

[0070] In this embodiment, firstly, 11 spatial form parameters of 22 real commercial pedestrian blocks in the target area are statistically analyzed (as shown in Figure 5 Seven parameters are selected for cluster analysis, which are street width, street length, building storey, building bay, building depth, courtyard bay and courtyard depth. Among the 22 block samples, there are 433 building samples and 29 courtyard layout samples. Since there are three parameters with different dimensions in the seven parameters, in order to ensure the accuracy and scientificity of the cluster analysis, the selected parameters are standardized to eliminate the differences between different dimension parameters. Specifically, the standardization is performed according to the mean and standard deviation of each parameter: ; wherein X is the standardized variable, x is any one of the seven parameters, is the mean of parameter x, is the standard deviation of variable x.

[0071] After the standardization according to the mean and standard deviation of each parameter, the weight of each parameter in the cluster analysis is balanced. The standardized results are shown in Table 2:

[0072] Table 2: Standardization of variable parameters of samples

[0073]

[0074] Further, the elbow rule is used to determine the optimal cluster number in the K-means clustering algorithm. The K-means clustering algorithm is used to cluster the standard block building data according to the optimal cluster number, and the best model conforming to the target commercial pedestrian street is obtained from the multiple commercial pedestrian street typical models (as shown in Figure 6 ). The best model has two, which are a small-scale best model, i.e. (a) in Figure 6 , and a large-scale best model, i.e. (b) in Figure 6 .

[0075] Specifically, due to the complexity and diversity of urban built environment, it is necessary to use statistical methods to analyze the relevant characteristics. K-means clustering algorithm is an iterative clustering technique widely used in data analysis field, its basic principle is to calculate the distance between data points and each cluster center by iteration, and according to these distances, data points are assigned to the nearest cluster center represented by the category. The goal of this algorithm is to minimize the difference within the cluster and maximize the difference between the clusters under the condition of a predetermined number of clusters K, so as to ensure that the data points belonging to the same cluster have high similarity, while the data points between different clusters show obvious difference. In the implementation of K-means clustering algorithm, the selection of initial cluster center is random, and then the algorithm adjusts the position of cluster center through iteration process until the convergence condition is met, that is, the position of cluster center no longer changes or the change degree is lower than a certain preset threshold. In each iteration, the algorithm calculates the distance from each data point to each cluster center, and reassigns the data points to the nearest cluster, and then updates the cluster center to the mean position of all data points in the cluster. Repeat the above steps until the algorithm stops. The operation steps are as follows:

[0076] (1) Randomly select k objects from n data as initial cluster centers;

[0077] (2) Calculate the Euclidean distance of each remaining data to the selected initial cluster center, and classify according to the minimum distance principle;

[0078] (3) Calculate the average value of each cluster data to its corresponding cluster center as the new cluster center;

[0079] (4) Repeat steps (2) and (3) until the cluster center no longer changes. After multiple iterations (d), the cluster center tends to be stable, which indicates that the cluster reaches the global or local stable state time cluster process is terminated.

[0080] At the same time, in order to accurately determine the optimal cluster number K in K-means clustering algorithm, the "elbow rule" is selected as the basis for decision making in this embodiment. The elbow rule is based on a key statistical indicator of cluster analysis, that is, the sum of squared errors (SSE), which measures the sum of distances from cluster center to cluster center, reflecting the consistency degree of cluster members. With the increase of K value, SSE will usually decrease, because the samples are assigned to more clusters, and the samples in each cluster are more closely. However, when K value reaches a certain point, the reduction rate of SSE will become slow, which is usually regarded as the indication of the best cluster number. From Figure 7It can be seen that when the value of K is 4, the sum of squared errors of clustering analysis SSE is significantly reduced and tends to be slow, indicating that the tightness of the cluster members and the number of clusters have reached a balance point. At this time, the value of K not only ensures that the samples in the cluster have high similarity, but also avoids the loss of information or the excessive complication of the clustering results caused by excessive subdivision. Therefore, the value of K is set to 4 in the clustering analysis of street length and width, in order to achieve the best balance between clustering effect and calculation efficiency.

[0081] Step S40, simulating the thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data.

[0082] Specifically, the 3D space data and the meteorological data are input into ENVI-met for simulation to generate the spatial distribution and the time distribution of the thermal environment.

[0083] The spatial distribution and the time distribution are evaluated for the thermal environment to obtain the thermal environment characteristics of the target commercial pedestrian street.

[0084] It can be understood that the ENVI-met simulation result is obtained by inputting the 3D space data such as urban geometry, building layout, street orientation, and vegetation distribution, and meteorological parameters such as temperature, humidity, wind speed, and solar radiation. By simulating these input data, the spatial and temporal distribution of the thermal environment is generated, and the impact of different design schemes on the local climate is evaluated.

[0085] In this embodiment, by summarizing and analyzing computer simulation software in related fields at home and abroad, and combining with the technical equipment situation, ENVI-met is finally used as a tool for microclimate simulation. ENVI-met is a high-level tool specially designed for simulating and analyzing the microclimate conditions of urban and surrounding environments, which can provide detailed and accurate microclimate simulation data. Secondly, ENVI-met has powerful functions and can simulate various microclimate environmental indicators, including but not limited to humidity, temperature, solar radiation, wind speed, and wind direction. These indicators are key factors for evaluating the thermal environment of urban streets, which can help to comprehensively understand and evaluate the microclimate changes under different urban forms. At the same time, ENVI-met provides a comprehensive tool and method to support the comparison and analysis of urban microclimate environment from urban form elements through scientific statistical methods, which means that ENVI-met can not only evaluate the current urban environment, but also predict the impact of future urban planning and building design changes on the microclimate. This prediction ability has important value for guiding future climate-adaptive urban design.

[0086] Step S50, adjusting the geometry of the target commercial pedestrian street based on the optimal model, and adjusting the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics.

[0087] The geometry of the target commercial pedestrian street includes building layout, street orientation, and 3D shape adjustment; the cooling equipment of the target commercial pedestrian street includes green plant covering system, spray cooling system, and sunshade system.

[0088] In this embodiment, the optimal building layout, the optimal street orientation, and the optimal 3D shape of the target commercial pedestrian street are obtained according to the optimal model.

[0089] Specifically, as shown in Figure 8 The building arrangement, building density, and building height of the target commercial pedestrian street are adjusted according to the optimal building layout.

[0090] It can be understood that by extracting the geometry of the representative block, the influence of the arrangement, density, and height of the building on the local thermal environment is determined. The height and density of the building will affect the ventilation, shadow area, and heat accumulation of the block. When adjusting the layout of the building, the air flow channel can be increased and the heat retention can be reduced according to the representative geometry, such as building spacing and interface density. For example, by reducing the building density or increasing the gap between buildings, the flow of natural wind is promoted, thereby reducing the heat island effect.

[0091] The street orientation of the target commercial pedestrian street is adjusted according to the optimal street orientation to reduce the accumulation of solar radiation heat.

[0092] It can be understood that the orientation of the street has a significant impact on the thermal environment, especially in high-density urban environments, the street orientation will affect the sunshine time and wind direction. According to the climate conditions of the target area, the north-south oriented street helps to reduce the accumulation of solar radiation heat and improve the ventilation effect. Therefore, in the typical geometry adjustment, the sunshine and overheating phenomenon can be reduced by optimizing the street orientation (such as adjusting the east-west orientation to the north-south orientation), especially in summer, to reduce the overheating problem of the pedestrian street.

[0093] The building shape coefficient and surface area ratio of the target commercial pedestrian street are adjusted according to the optimal 3D shape.

[0094] It can be understood that the 3D shape characteristics such as building shape coefficient, surface area ratio, etc. have a significant impact on heat accumulation in the thermal environment. By optimizing the shape of the building (such as reducing the design of the building with complex facades), the surface area exposed to solar radiation is reduced, thereby reducing heat accumulation.

[0095] Further, the temperature of each area in the target commercial pedestrian street is determined according to the thermal environment characteristics, and a target area with a temperature exceeding a preset threshold is obtained, the green plant coverage rate of the green plant coverage system in the target area is increased, and the sun-shading facility of the sun-shading system in the target area is increased.

[0096] Greening plays a crucial role in urban thermal environment. According to the analysis of thermal environment characteristics, plants can not only reduce temperature through transpiration, but also provide shade and reduce heat accumulation on the ground and buildings. By increasing the green plant coverage rate in the pedestrian street area, such as setting green plants on both sides of the road or planting trees in the building gap, the temperature can be effectively reduced and the thermal comfort can be increased. In this embodiment, the temperature of each area in the target commercial pedestrian street is determined according to the thermal environment characteristics, and it is determined which areas have a temperature that is too high and air flow is poor, and the greening can be preferentially increased. For example, tall trees are planted on the south side of the street where the sunlight is strong, or a green belt is set around the square to reduce heat radiation. Sun-shading facilities such as sunshades and adjustable shutters can reduce solar radiation into the street and avoid overheating in local areas. These facilities can be flexibly adjusted according to the solar angle and thermal environment characteristics, especially in the strong sunlight in the afternoon, to provide a space for pedestrians to avoid the heat.

[0097] A spray cooling system is arranged in the target area to increase the air humidity of the target area by regularly spraying fine water mist.

[0098] The spray cooling system is an active cooling means for increasing the local air humidity and reducing the temperature by spraying fine water mist. Based on the analysis of the thermal environment, the spray system can be installed in areas with serious heat accumulation and poor air flow, such as the middle section of the square and the open pedestrian street. In this embodiment, when the spray system is arranged in the pedestrian street area, the research will be based on the thermal environment simulation data to identify areas with high temperature or high pedestrian flow, and then the local temperature can be reduced by regular or intelligent spraying to provide a more comfortable walking experience.

[0099] According to the experimental verification, after implementing the above optimization measures, the average temperature in the street area is reduced by 2.5℃, the relative humidity is increased by 5%, and the wind speed is increased by 10%. The comfort score of the street area by pedestrians is increased by 20%.

[0100] Further, in another embodiment of the present application, another commercial pedestrian street of the target area in the east-west direction is selected for research, the street area is 3000 square meters, the street width is 8 meters, and the building height is uniform.

[0101] The optimization steps are as follows:

[0102] Data collection: Collect relevant data using automatic weather stations and building facade sensors; Extract 2D and 3D morphological indicator data for the block.

[0103] Data analysis: Evaluate the relationship between 2D and 3D morphological indicators and thermal environment parameters using Spearman correlation analysis; Identify key thermal environment influencing factors such as building shape coefficient and street orientation.

[0104] Optimization design: Modify street layout and increase building spacing to improve wind speed.

[0105] Configure timed misting system and automatically adjust sunshade canopy to optimize thermal environment.

[0106] Effect verification: After optimization, solar radiation intensity in the block is reduced by 15%, air temperature is reduced by 3℃, pedestrian comfort in the block is improved by 25%, and heat island effect is significantly reduced.

[0107] In another embodiment of the present application, a commercial pedestrian street in the target area is selected for comprehensive optimization research, with an area of 6000 square meters, and the street width and building height vary greatly.

[0108] The optimization steps are:

[0109] Data collection: Collect meteorological data and spatial morphological data, including building height, street width, green coverage, etc.

[0110] Data analysis: Comprehensive use of K-means clustering analysis method and Spearman correlation analysis method to evaluate the thermal environment effect of different models; Identify key thermal environment influencing factors such as building layout, street geometry and green configuration.

[0111] Optimization design: Adjust street layout and building height, increase green coverage, set environmental regulation equipment; Use ENVI-met simulation to evaluate the thermal environment effect of the comprehensive optimization scheme.

[0112] Effect verification: After comprehensive optimization, the thermal comfort in the block is improved by 20%, the high temperature area is reduced by 25%; Pedestrian overall satisfaction with the pedestrian street is improved by 30%, and the thermal environment quality is significantly improved.

[0113] The present application can bring the following beneficial effects:

[0114] (1) The present application can significantly improve thermal comfort, by systematically analyzing and optimizing the geometric shape and thermal environment data of the target area commercial pedestrian street, the present application effectively improves the thermal comfort in the block. The research results show that the block designed by the model of the present application can significantly reduce the air temperature and sensible heat temperature in the local area in the high temperature season, and improve the thermal comfort felt by pedestrians, and reduce the high temperature discomfort.

[0115] (2) The present application can more accurately control key factors such as solar radiation, wind speed and relative humidity of the block, and optimize the thermal environment distribution by introducing the correlation analysis of 3D form indicators and thermal environment parameters. This fine thermal environment regulation helps to reduce the urban heat island effect and improve the ecological environment quality of the block.

[0116] (3) The present application achieves significant energy saving effect without increasing the energy consumption of additional equipment. Compared with the traditional design method, the present application reduces the dependence on air conditioning and other cooling equipment, reduces energy consumption and carbon emissions, and is environmentally friendly.

[0117] (4) The model of the present application provides the best solution for various form configurations, which can be flexibly applied to the design of commercial pedestrian streets in different geographical locations and climate conditions. Whether it is a north-south oriented block or an east-west oriented block, the present application can realize the optimization of thermal environment through reasonable form design strategy, making the design more adaptable and flexible.

[0118] (5) The present application significantly improves the overall space quality of the commercial pedestrian street through reasonable form design and thermal environment optimization measures, and enhances the walking experience of citizens and tourists. The block after optimization design can effectively reduce the occurrence of high temperature area, provide more pleasant outdoor activity space, and promote the utilization rate of urban public space.

[0119] Further, as shown in Figure 6 based on the above temperature adjustment method based on the thermal comfort of commercial pedestrian street, the present application also correspondingly provides a temperature adjustment system based on the thermal comfort of commercial pedestrian street, wherein the temperature adjustment system based on the thermal comfort of commercial pedestrian street comprises:

[0120] A typical model construction module 61 is used to statistically analyze the form characteristics of commercial pedestrian streets in the target area where the target commercial pedestrian street is located, and obtain a plurality of typical models of commercial pedestrian streets in the target area.

[0121] A data acquisition module 62 is used for block building data, 3D space data and meteorological data of the target commercial pedestrian street.

[0122] An optimal model acquisition module 63 is used for clustering processing of the block building data, and obtaining the best model from a plurality of typical models of commercial pedestrian streets.

[0123] A thermal environment feature generation module 64 is used to simulate the thermal environment features of the target commercial pedestrian street according to the 3D space data and the meteorological data.

[0124] The comfort optimization module 65 is configured to adjust the geometry of the target commercial pedestrian street based on the optimal model and to adjust the cooling equipment of the target commercial pedestrian street based on the thermal environment characteristics.

[0125] Further, as shown in Figure 7 Based on the above-mentioned temperature adjustment method and system based on the thermal comfort of commercial pedestrian street, the application also provides a terminal, which comprises a processor 10, a memory 20 and a display 30. Figure 7 Only some components of the terminal are shown, but it should be understood that all the shown components are not required, and more or less components can be alternatively implemented.

[0126] The memory 20 can be an internal storage unit of the terminal in some embodiments, such as a hard disk or a memory of the terminal. The memory 20 can also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 20 can include both the internal storage unit and the external storage device of the terminal. The memory 20 is configured to store application software and various data installed on the terminal, such as program codes of the terminal, etc. The memory 20 can also be configured to temporarily store data that has been output or will be output. In an embodiment, the memory 20 stores a temperature adjustment program based on the thermal comfort of commercial pedestrian street 40, which can be executed by the processor 10 to implement the temperature adjustment method based on the thermal comfort of commercial pedestrian street in the application.

[0127] The processor 10 can be a central processing unit (CPU), a microprocessor or other data processing chip in some embodiments, which is configured to run program codes or process data stored in the memory 20, such as to execute the temperature adjustment method based on the thermal comfort of commercial pedestrian street, etc.

[0128] The display 30 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. in some embodiments. The display 30 is configured to display information of the terminal and to display a visualized user interface. The components 10-30 of the terminal communicate with each other through a system bus.

[0129] In an embodiment, the following steps are implemented when the processor 10 executes the temperature adjustment program 40 based on the commercial pedestrian street thermal comfort in the memory 20:

[0130] statistically analyzing the morphological characteristics of the commercial pedestrian streets in the target region where the target commercial pedestrian street is located to obtain a plurality of typical models of the commercial pedestrian streets in the target region;

[0131] collecting block building data, 3D space data, and meteorological data of the target commercial pedestrian street;

[0132] performing clustering processing on the block building data to obtain an optimal model from the plurality of typical models of the commercial pedestrian streets;

[0133] simulating thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data;

[0134] adjusting the geometric morphology of the target commercial pedestrian street based on the optimal model and adjusting the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics.

[0135] wherein the block building data, the 3D space data, and the meteorological data are collected by a sensor network;

[0136] the block building data includes street width, street length, building story, building bay, building depth, courtyard bay, and courtyard depth;

[0137] the 3D space data includes geometric morphology, building layout, street orientation, and vegetation distribution;

[0138] the meteorological data includes temperature, humidity, wind speed, and solar radiation.

[0139] wherein the clustering processing on the block building data to obtain an optimal model from the plurality of typical models of the commercial pedestrian streets specifically includes:

[0140] respectively calculating the mean and standard deviation of each parameter in the block building data, and performing standardization processing on each parameter in the block building data according to the mean and the standard deviation to obtain standard block building data;

[0141] determining the optimal cluster number in the K-means clustering algorithm by elbow rule, and performing clustering on the standard block building data according to the optimal cluster number by the K-means clustering algorithm to obtain an optimal model from the plurality of typical models of the commercial pedestrian streets that conforms to the target commercial pedestrian street.

[0142] wherein the simulating thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data specifically includes:

[0143] inputting the 3D space data and the meteorological data into ENVI-met for simulation to generate spatial distribution and time distribution of thermal environment;

[0144] performing thermal environment evaluation on the spatial distribution and the time distribution to obtain thermal environment characteristics of the target commercial pedestrian street.

[0145] The geometric form includes building layout, street orientation and 3D form adjustment.

[0146] The cooling equipment includes a green plant covering system, a spray cooling system and a sunshade system.

[0147] The adjustment of the geometric form of the target commercial pedestrian street according to the optimal model specifically includes:

[0148] The optimal building layout, the optimal street orientation and the optimal 3D form of the target commercial pedestrian street are obtained according to the optimal model.

[0149] The building arrangement mode, the building density and the building height of the target commercial pedestrian street are adjusted according to the optimal building layout.

[0150] The street orientation of the target commercial pedestrian street is adjusted according to the optimal street orientation to reduce solar radiation heat accumulation.

[0151] The building shape coefficient and the surface of the target commercial pedestrian street are adjusted according to the optimal 3D form. The adjustment of the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics specifically includes:

[0152] The temperature of each area in the target commercial pedestrian street is determined according to the thermal environment characteristics, and a target area with temperature exceeding a preset threshold is obtained.

[0153] The green plant coverage of the green plant covering system in the target area is increased, and the sunshade facilities of the sunshade system in the target area are increased.

[0154] The spray cooling system is arranged in the target area, and the air humidity of the target area is increased by regularly spraying fine water mist.

[0155] In summary, the present application provides a temperature adjustment method and system based on the thermal comfort of commercial pedestrian streets, the method comprising: statistically analyzing the morphological characteristics of commercial pedestrian streets in a target area where a target commercial pedestrian street is located to obtain a plurality of typical models of commercial pedestrian streets in the target area; collecting street block building data, 3D space data and meteorological data of the target commercial pedestrian street; clustering the street block building data to obtain an optimal model from the plurality of typical models of commercial pedestrian streets; simulating the thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data; adjusting the geometric shape of the target commercial pedestrian street based on the optimal model, and adjusting the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics. The present application dynamically adjusts the spatial layout and environmental parameters of the commercial pedestrian street block by combining multi-source environmental data, climate conditions and urban morphological characteristics, so as to improve the thermal comfort and use experience of the pedestrian street block. It can be further applied to urban planning, public space design and the development of climate change response strategies, and is suitable for the design and optimization of commercial pedestrian streets, public squares and other urban open spaces in high-temperature seasons and climate-varying regions.

[0156] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that processes, methods, articles or terminals including a series of elements not only include those elements, but also include other elements not explicitly listed, or include elements inherent to such processes, methods, articles or terminals. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0157] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the computer program can include the processes of the above-mentioned embodiments of the method. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0158] It should be understood that the application is not limited to the above examples, and those skilled in the art can make improvements or changes according to the above description, and all these improvements and changes shall fall within the protection scope of the appended claims of the present application.

Claims

1. A temperature adjustment method based on thermal comfort of a commercial pedestrian street, characterized by, The temperature adjustment method based on the thermal comfort of the commercial pedestrian street comprises the following steps: statistically analyzing the morphological characteristics of commercial pedestrian streets in a target region where a target commercial pedestrian street is located to obtain a plurality of typical models of commercial pedestrian streets in the target region; the typical model of the commercial pedestrian street abstracts and simplifies the typical characteristics of the urban block in spatial layout, building morphology, street width, height, and green coverage, and analyzes or predicts the change characteristics of the microclimate through interaction with climate elements; collecting block building data, 3D space data, and meteorological data of the target commercial pedestrian street; performing clustering processing on the block building data to obtain a best model from a plurality of typical models of commercial pedestrian streets; simulating the thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data; the simulation of the thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data specifically comprises: inputting the 3D space data and the meteorological data into ENVI-met for simulation to generate spatial distribution and temporal distribution of the thermal environment; performing thermal environment evaluation on the spatial distribution and the temporal distribution to obtain the thermal environment characteristics of the target commercial pedestrian street; adjusting the geometric form of the target commercial pedestrian street based on the best model, and adjusting the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics; the geometric form includes building layout, street orientation, and 3D form adjustment; the cooling equipment includes green plant coverage system, spray cooling system, and sunshade system; the adjustment of the geometric form of the target commercial pedestrian street according to the best model specifically comprises: obtaining the best building layout, the best street orientation, and the best 3D form of the target commercial pedestrian street according to the best model; adjusting the building arrangement, building density, and building height of the target commercial pedestrian street according to the best building layout; adjusting the street orientation of the target commercial pedestrian street according to the best street orientation to reduce the accumulation of solar radiation heat; adjusting the building shape coefficient and surface area ratio of the target commercial pedestrian street according to the best 3D form.

2. The temperature adjustment method based on thermal comfort of a business pedestrian street according to claim 1, wherein, The block building data, the 3D space data, and the meteorological data are collected by a sensor network; the block building data includes street width, street length, building story, building bay, building depth, courtyard bay, and courtyard depth; the 3D space data includes geometric form, building layout, street orientation, and vegetation distribution; the meteorological data includes temperature, humidity, wind speed, and solar radiation.

3. The temperature adjustment method based on thermal comfort of a business pedestrian street according to claim 1, wherein, the clustering processing of the block building data to obtain a best model from a plurality of typical models of commercial pedestrian streets specifically comprises: respectively calculating the mean and standard deviation of each parameter in the block building data, standardizing each parameter in the block building data according to the mean and the standard deviation to obtain standard block building data; The optimal cluster number in the K-means clustering algorithm is determined by the elbow rule, and the standard block building data is clustered according to the optimal cluster number by the K-means clustering algorithm, so as to obtain the best model from the multiple commercial pedestrian street typical models that conforms to the target commercial pedestrian street.

4. The temperature adjustment method based on thermal comfort of a business pedestrian street according to claim 1, wherein, The adjustment of the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics specifically includes: The temperature of each area in the target commercial pedestrian street is determined according to the thermal environment characteristics, and a target area with a temperature exceeding a preset threshold is obtained; The green plant coverage rate of the green plant coverage system in the target area is increased, and the sun-shading facilities of the sun-shading system in the target area are increased; A spray cooling system is arranged in the target area, and the air humidity of the target area is increased by regularly spraying fine water mist.

5. A temperature adjustment system based on thermal comfort of a commercial pedestrian street, characterized by, The temperature adjustment system based on the thermal comfort of a commercial pedestrian street is applied to the temperature adjustment method based on the thermal comfort of a commercial pedestrian street in any one of claims 1-4, and the temperature adjustment system based on the thermal comfort of a commercial pedestrian street comprises: A typical model construction module is configured to statistically analyze the morphological characteristics of commercial pedestrian streets in a target region where a target commercial pedestrian street is located, and obtain multiple commercial pedestrian street typical models of the target region; A data acquisition module is configured to acquire block building data, 3D space data and meteorological data of the target commercial pedestrian street; An optimal model acquisition module is configured to cluster the block building data, and obtain an optimal model from the multiple commercial pedestrian street typical models; A thermal environment characteristic generation module is configured to simulate the thermal environment characteristics of the target commercial pedestrian street according to the 3D space data and the meteorological data; A comfort optimization module is configured to adjust the geometric shape of the target commercial pedestrian street based on the optimal model, and adjust the cooling equipment of the target commercial pedestrian street according to the thermal environment characteristics.

6. A terminal, characterized by comprising: The terminal comprises a memory, a processor and a temperature adjustment program based on the thermal comfort of a commercial pedestrian street stored on the memory and executable on the processor, and the temperature adjustment program based on the thermal comfort of a commercial pedestrian street is executed by the processor to implement the steps of the temperature adjustment method based on the thermal comfort of a commercial pedestrian street in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a temperature adjustment program based on the thermal comfort of a commercial pedestrian street, and the temperature adjustment program based on the thermal comfort of a commercial pedestrian street is executed by the processor to implement the steps of the temperature adjustment method based on the thermal comfort of a commercial pedestrian street in any one of claims 1-4.

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