Graphical heterogeneous texture urban wind energy development suitability evaluation method and system

Abstract

The invention provides a graphical heterogeneous texture urban wind energy development suitability evaluation method and system, and the method comprises the steps: firstly, carrying out the urban morphological analysis; the method comprises the following steps: sequentially considering a surrounding block shielding effect and a single building wake flow effect from block and building scales, so as to roughly and quickly evaluate the suitability of wind energy development; secondly, computational fluid dynamics (CFD) simulation is conducted, the wind power density of each building roof layer is quantified through the simulation, and then accurate evaluation of wind energy potential distribution is achieved; the method is suitable for system evaluation of urban low-wind-speed wind energy development suitability, research results of influence of urban forms on boundary layer airflow are effectively converted, the requirement for quick response in the preliminary evaluation stage is particularly met, and decision reference on the urban design level can be provided for wind energy utilization planning of low-carbon cities in the future.

Description

Technical Field

[0001] The present invention belongs to the field of low wind speed wind energy development and utilization, and specifically relates to a graphically constructed method and system for evaluating the suitability of wind energy development in heterogeneous urban areas, and in particular to a graphically constructed program for evaluating the suitability of wind energy development in heterogeneous urban areas. Background Art

[0002] Rapid urbanization has significantly reshaped the morphological structure of Chinese cities. Currently, many large and medium-sized cities exhibit high average building heights and a high rate of height variability. Compared to Europe and the United States, my country boasts a significantly higher number of skyscrapers, with over 3,400 buildings over 150 meters tall, more than three times the number in the United States. In addition to the upward trend in commercial and office complexes, Chinese cities are also experiencing a trend toward high-rise residential blocks, a stark contrast to the predominantly low-rise residential structure in European and American cities. In the early days of large-scale urban construction, due to the absence of height control policies, with the exception of cities like Suzhou and Xi'an, which implemented strict height restrictions in their ancient urban areas, the average rate of change in building height in some urban areas is generally high, and vertical heterogeneity is very pronounced.

[0003] From an environmental perspective, unbridled vertical urban expansion has brought considerable negative effects, such as reduced canopy air circulation, exacerbated urban heat island effects, and increased air pollution. This has been extensively discussed in related research. However, from an energy perspective, taller buildings also have positive benefits. The unique aerodynamic properties of tall buildings provide favorable conditions for harnessing wind energy on high rooftops and in areas with high local wind speeds.

[0004] Compared to wind-rich areas like coastal and mountainous regions, urban wind speeds within the boundary layer and canopy layer are relatively low. However, with the continuous advancement of low-speed wind power and other wind energy technologies, urban wind energy is expected to play a significant role in the development of future low-carbon cities.

[0005] For example, patent document CN107194141A discloses a regional wind energy resource refined assessment model, the steps of which are as follows: S1: using the observation data of wind towers, SCADA data of wind turbines and terrain parameters belonging to each small-scale wind farm, to establish independent small-scale regional multi-reference point wind energy resource assessment models; the range of the small-scale wind farm is 1-20km; S2: using the meteorological station observation data contained in the regional range of 20-200km and the existing model in step S1 to establish an association model, and obtain the corresponding weight coefficient to establish a dynamic model; S3, using numerical weather forecast data to establish a mesoscale model of the regional range of 200-500km; S3: using the mesoscale model, wind farm power prediction system and GIS geographic information model and the existing models in steps S1 and S2 to establish a refined adaptive model; S4: combining the refined adaptive model with the power load scheduling system to achieve refined regional wind energy assessment and visualized dynamic scheduling management.

[0006] For example, patent document CN116306026A discloses a wind energy resource assessment method, device and storage medium for complex terrain, the method comprising the following steps: (1) generating a climate field based on wind speed observation data; (2) generating an anomaly field; (3) superimposing the climate field and anomaly field results with consistent spatial resolution to obtain a high-precision wind speed interpolation result; (4) performing deviation correction on the obtained interpolation result and the wind speed observation data to obtain the final result; (5) calculating the average effective wind power density; (6) calculating the estimated wind energy density based on the daily average wind speed; the present invention can effectively improve the accuracy of wind speed data; effectively reduce the system error caused by excessively coarse spatial resolution; effectively improve the spatial distribution of wind speed data; can assess wind energy resources in various situations such as complex terrain and lack of hourly wind speed data; can establish a high-precision wind energy resource data set, and effectively improve the assessment accuracy of wind energy resources.

[0007] For example, a paper published in the journal "Progress in Electric Power and Energy" titled "Study on Urban Building Wind Environment Simulation and Wind Energy Utilization" uses Fluent computational fluid dynamics to numerically simulate the wind environment around the main building complex of North China Electric Power University to explore the feasibility of wind power generation in this area. During the research process, the paper first used Gambit software to perform geometric modeling. Next, the paper analyzed the characteristics of wind energy distribution in urban building environments and designed a dense meshing scheme for areas with dense wind energy distribution and complex flow. In particular, a detailed analysis was conducted on possible installation locations of wind turbines in building environments, such as alleys, rooftops, and corners. Finally, to address the issues of wind intensification and concentration in urban building wind energy utilization, the paper comprehensively considered different wind energy utilization methods and building wind environments, proposed wind turbine modification design requirements suitable for urban wind energy utilization, and introduced the "concentration concept" for the first time in the field of urban building wind energy utilization to improve wind intensification and concentration.

[0008] However, in existing technologies, most solutions for urban wind assessment use wind tunnel experiments or computational fluid dynamics (CFD) simulations. However, these wind assessment methods have the following limitations in meeting different timeliness and accuracy requirements:

[0009] 1. Existing technologies fail to consider the phased nature of wind assessment work and only adopt a unified assessment strategy, ignoring the phased differences in accuracy, response speed, and resource input, which affects the scientificity and practicality of the overall assessment work.

[0010] 2. Existing technologies ignore the high timeliness requirements of the early design stages of wind power development projects and rely too much on systematic and high-cost methods to obtain wind farm data. This makes it difficult to achieve cost reduction and efficiency improvement when facing multiple new projects, thus restricting the efficiency and economy of early decision-making in wind energy development.

[0011] 3. Existing technologies lack the ability to summarize and utilize urban wind field patterns, and overemphasize obtaining microscopic and detailed wind speed data for individual cases. Due to limitations in computing power and cost, they are not suitable for conducting suitability assessments for wind energy development in large-scale heterogeneous urban areas. Summary of the Invention

[0012] In view of the defects in the prior art, the purpose of the present invention is to provide a graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas.

[0013] The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas provided by the present invention includes:

[0014] Step S1: constructing a building database based on vector data;

[0015] Step S2: perform a rough assessment of the building database;

[0016] Step S3: Conduct urban morphology analysis;

[0017] Step S4: Let the average frontal area ratio of the block be f The graphic represents a high-suitability neighborhood;

[0018] Step S5: let the wake superimposed graphic represent the high suitability building;

[0019] Step S6: perform a rough suitability assessment;

[0020] Step S7: Determine whether accurate evaluation is required. If yes, jump to step S8; if no, jump to step S9;

[0021] Step S8: performing computational fluid dynamics analysis;

[0022] Step S9: Output the result and end.

[0023] Preferably, step S1 has low requirements for the integrity of the geometric representation of the building volume in the data file, and the geometric representation of the building volume includes: open surfaces and closed volumes; the building database includes: building base outlines and height information; the building database generates a minimum rectangular volume of each building parallel or perpendicular to the wind direction based on a bounding box method; the leeward side facade of the minimum rectangular volume is always perpendicular to the wind direction and serves as a reference plane for drawing the wake area.

[0024] Preferably, constructing a building database based on vector data in step S1 includes: drawing a wake area in the building database based on the height H of each individual building, and the shape of the drawn wake area includes: an elliptical cone shape and a truncated cone shape; the truncated cone shape specifically means that when the target building is a cube or the facade perpendicular to the wind direction is a square, the wake area appears as a truncated cone; the elliptical cone shape specifically means that the top surface of the elliptical cone starts from the leeward facade of the building, with the height and width of the building as the two axes of the ellipse; the rotation axis of the elliptical cone starts from the center point of the leeward facade, extends outward along the normal direction of the facade, and has a length of 5 to 15 times the height H; the size of the bottom surface of the elliptical cone is 1.5 to 2 times the size of the top surface.

[0025] Preferably, step S2 requires that the building be represented as a closed geometric volume and allows reasonable simplification of changes in the size of building details; further, both steps S1 and S2 rely on an urban building database, which contains electronic vector files, including: shp, dwg, and 3dm.

[0026] Preferably, the urban morphology analysis in step S3 includes: quantitative analysis of the average windward area ratio of blocks and quantitative analysis of building heights;

[0027] The calculation formula for the quantitative analysis of the average windward area ratio of the block is as follows:

[0028] λ f =A f / A S

[0029] in,

[0030] λ f It is expressed as the average windward area ratio of the block and is dimensionless;

[0031] A f Expressed as the area of ​​the windward side facade, unit is m 2 ;

[0032] A S Expressed as the area of ​​the block base in m 2 ;

[0033] When considering the wind direction θ on λ f When considering the impact of , the calculation formula for the quantitative analysis of the average windward area ratio of the block is as follows:

[0034] λ f,θ =A f,θ / A s

[0035] in,

[0036] λ f,θ It is expressed as the average windward area ratio of the block under the wind direction θ, which is dimensionless;

[0037] A f,θ It is expressed as the projected area of ​​the windward side facade on the normal surface perpendicular to the wind direction, considering the wind direction θ, in m 2 , except for a few cylindrical towers, A f,θ It will change with the wind direction θ;

[0038] A s It is expressed as the area of ​​the block base under the wind direction θ, in m 2 ;

[0039] Furthermore, the urban morphology analysis in step S3 includes: evaluating whether the target block is suitable for wind energy development, focusing on the evaluation of the surrounding blocks λ in the graphical and quantitative analysis. f,θ size, when the surrounding blocks λ f,θ When the overall size is small, the target block is shielded by a weaker effect and is suitable for wind energy development; when the surrounding blocks are f,θ When the overall area is large, the target block will be subject to a stronger shading effect, insufficient wind energy, and poor development suitability.

[0040] Preferably, the urban morphological analysis in step S3 includes: when conducting statistics on the windward area ratio at the block scale, statistics on the local dominant wind direction or multiple wind directions can be performed according to specific needs, the windward area ratio can reflect the average value of the overall situation of each block, and the windward area ratio can assist in calculating the projected area of ​​the windward side facade on the plane perpendicular to the wind direction; the windward area ratio includes: manual identification of the windward surface, rapid identification using a parametric method, when it is determined that the facade whose normal direction is at an obtuse angle to the wind direction is the windward surface, that is, the wind direction θ>90°, but excluding the wind direction θ=180°, the calculation formula of the projected area is as follows:

[0041] A f,θ =sin(θ-90°)A f

[0042] When the wind direction θ=180°, the facade and the wind direction are perpendicular to each other.

[0043] Preferably, the urban morphology analysis in step S3 includes:

[0044] Step S301: Calculate the average windward area ratio λ of the block f and height statistics;

[0045] Step S302: Identify low shadowing effect areas at the block scale;

[0046] Step S303: Identify the weak wake impact area at the building scale.

[0047] Preferably, the computational fluid dynamics analysis performed in step S8 includes:

[0048] Step S801: performing high-resolution RANSCFD simulation;

[0049] Step S802: performing three-dimensional flow field analysis;

[0050] Step S803: quantifying the wind energy potential of the roof layer and representing it as a wind power density graph;

[0051] Step S804: performing accurate wind energy assessment;

[0052] Furthermore, the high-resolution RANSCFD simulation performed in step S801 specifically refers to performing computational fluid dynamics simulation based on the Reynolds-averaged Navier-Stokes equations. The Reynolds-averaged Navier-Stokes equations model can simulate urban boundary layer airflow. Factors to consider in the urban boundary layer airflow simulation include: computational domain, boundary conditions, and grid method. When the urban boundary layer airflow simulates the neutral atmospheric boundary layer velocity, the neutral atmospheric boundary layer velocity conforms to a logarithmic function form, as shown below:

[0053] U(Z)=(u* / κ)ln((Z+Z0) / Z0)

[0054] in,

[0055] Z represents the height in meters;

[0056] U(Z) represents the wind speed in the atmospheric boundary layer at height Z, that is, the wind velocity;

[0057] u * Expressed as friction velocity in m / s;

[0058] κ is the Karman constant, for example, 0.4;

[0059] Z0 represents the roughness length of the underlying surface, in m;

[0060] Furthermore, the high-resolution RANSCFD simulation in step S801 further includes: analyzing the flow velocity distribution of the roof layer; the analyzing the flow velocity distribution of the roof layer includes: based on the wind velocity result obtained by analysis, further performing calculations to obtain wind energy density, and then plotting the obtained wind energy density calculation results into an isovalue cloud map to intuitively display the differences in wind energy potential of different building roofs. The calculation formula is as follows:

[0061] PD=0.5ρU 3

[0062] in,

[0063] ρ is the air density in kg / m 3 ;

[0064] U represents the air velocity in m / s;

[0065] Furthermore, the high-resolution RANSCFD simulation is performed in step S801, specifically, generating a grid of appropriate accuracy based on the three-dimensional volume model of urban buildings, setting a reasonable calculation domain and boundary conditions, using the RANS model to carry out simulation analysis, and calculating the wind energy density in the post-processing step based on the obtained flow field velocity results.

[0066] The present invention provides a graphical system for evaluating the suitability of wind energy development in heterogeneous urban areas, comprising:

[0067] Module M1: Constructing a building database based on vector data;

[0068] Module M2: Rough assessment of the building database;

[0069] Module M3: Conducting urban morphological analysis;

[0070] Furthermore, the urban morphology analysis in the module M3 includes:

[0071] Module M301: Calculate the average frontal area ratio λ of the block f and height statistics;

[0072] Module M302: Identify low shadowing effect areas at the block scale;

[0073] Module M303: Identify weak wake impact areas at the building scale;

[0074] Module M4: Let the average frontal area ratio of the block be λ f The graphic represents a high-suitability neighborhood;

[0075] Module M5: Let the wake overlay diagram represent high suitability buildings;

[0076] Module M6: Conduct a rough suitability assessment;

[0077] Module M7: Determine whether a precise assessment is needed;

[0078] Module M8: Perform computational fluid dynamics analysis;

[0079] Furthermore, the computational fluid dynamics analysis performed in the module M8 includes:

[0080] Module M801: performing high-resolution RANSCFD simulation, wherein the high-resolution RANSCFD simulation specifically refers to performing computational fluid dynamics simulation based on the Reynolds-averaged Navier-Stokes equations;

[0081] Module M802: Perform three-dimensional flow field analysis;

[0082] Module M803: Quantify the wind energy potential of the roof layer and present it as a wind power density diagram;

[0083] Module M804: Conducting accurate wind energy assessment;

[0084] Module M9: Output the results and end.

[0085] The present invention provides a device for a graphically-designed heterogeneous texture urban area wind energy development suitability assessment system, which realizes the graphical representation of wind energy potential distribution through the heterogeneous texture urban area wind energy development suitability assessment.

[0086] Compared with the prior art, the present invention has the following beneficial effects:

[0087] 1. The present invention can take into account both rough and precise assessments, and is a systematic assessment solution that can provide more scientific and reliable support for comprehensive decision-making on wind energy development.

[0088] 2. This paper addresses the urgent need for timely preliminary assessments of urban wind energy suitability by proposing a rough assessment method. Specifically, by comprehensively considering the shading effects of surrounding high-rise blocks and the wake effects of individual high-rise buildings, a wind analysis method suitable for urban areas with large height variations and heterogeneous textures is constructed. This approach addresses the practical challenges of quantifying and assessing the relationship between urban form and ventilation performance, providing an efficient and feasible strategy with significant research and practical value.

[0089] 3. The present invention graphically processes the assessment of wind energy development suitability, providing a decision-making reference at the urban design level for future low-carbon urban wind energy utilization planning, and can further serve as a shared platform for multi-professional and multi-trade project collaboration. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0091] Figure 1 This is a schematic flow chart of the method for evaluating the suitability of wind energy development in heterogeneous urban areas proposed by the present invention;

[0092] Figure 2 A schematic diagram of a building geometry database for the graphically illustrated method for assessing the suitability of wind energy development in heterogeneous urban areas proposed in the present invention;

[0093] Figure 3 This is an example of the method for evaluating the suitability of wind energy development in a heterogeneous urban area proposed by the present invention, showing the distribution of windward area ratios of blocks in an urban area under different wind directions;

[0094] Figure 4 This is a box diagram of the distribution of windward area ratios of surrounding blocks of each target block in an example of the method for evaluating the suitability of wind energy development in a heterogeneous urban area proposed in the present invention;

[0095] Figure 5 This is a schematic diagram of the superposition of wind shadow areas of urban buildings in an example of the method for evaluating the suitability of wind energy development in a heterogeneous urban area proposed by the present invention;

[0096] Figure 6 This is a schematic diagram of the wind energy density distribution on the roof layer of an example urban building proposed by the present invention. DETAILED DESCRIPTION

[0097] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0098] The present invention provides a graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas, comprising:

[0099] Step S1: constructing a building database based on vector data;

[0100] Furthermore, the step S1 has a low requirement for the integrity of the building volume geometric representation in the data file, wherein the building volume geometric representation includes: open surface and closed volume; the construction of the vector data can construct a three-dimensional urban building volume model through the GIS / CAD / RHINO platform;

[0101] Furthermore, the step S1 of constructing a building database based on the vector data includes:

[0102] The building database draws the wake area based on the height H of each individual building. The shape of the drawn wake area includes: an elliptical cone shape and a truncated cone shape. The truncated cone shape includes: when the target building is a cube or the facade perpendicular to the wind direction is a square, the wake area appears as a truncated cone; the elliptical cone shape specifically means that the top surface of the elliptical cone starts from the leeward facade of the building, with the building height and width as the two axes of the ellipse; the rotation axis of the elliptical cone starts from the center point of the leeward facade and extends outward in the normal direction of the facade, with a length of 5 to 15 times the height H; the size of the bottom surface of the elliptical cone is 1.5 to 2 times the size of the top surface;

[0103] Preferably, the drawing of the wake area includes: drawing the wake areas of all buildings in the study area; if the roof of a building is higher than the spatial range of the superposition of the wake areas, it is considered that the roof of the building is less affected by the wake effect of the upwind building, has a large wind energy potential, and is suitable for wind energy development; if the roof of the building is covered by the superposition area of ​​the wake, it is considered that it is not suitable for wind energy development;

[0104] Preferably, when considering different wind directions, the buildings in the building database have two or more leeward sides, and the leeward sides are not completely perpendicular to the wind direction;

[0105] Furthermore, the building database includes: building base outlines and height information; the building database generates a minimum rectangular parallelepiped volume for each building that is parallel or perpendicular to the wind direction based on a bounding box method; the leeward side elevation of the minimum rectangular parallelepiped volume is always perpendicular to the wind direction and serves as a reference plane for drawing the wake area;

[0106] Step S2: perform a rough assessment of the building database;

[0107] Furthermore, the step S2 requires that the building be represented as a closed geometric volume and that reasonable simplification of the size variation of the building details be allowed, for example, the size variation of the building details is less than 2m;

[0108] Furthermore, both step S1 and step S2 rely on a city building database, which contains electronic vector files, including shp, dwg, and 3dm.

[0109] Step S3: Conduct urban morphology analysis;

[0110] Furthermore, the urban morphology analysis in step S3 includes: quantitative analysis of the average windward area ratio of blocks (frontalarea density) and quantitative analysis of building heights;

[0111] The calculation formula for the quantitative analysis of the average windward area ratio of the block is as follows:

[0112] λ f =A f / A S

[0113] in,

[0114] λ f It is expressed as the average windward area ratio of the block and is dimensionless;

[0115] A f Expressed as the area of ​​the windward side facade, unit is m 2 ;

[0116] A S Expressed as the area of ​​the block base in m 2 .

[0117] If we consider the wind direction θ to λ f The calculation formula for the quantitative analysis of the average windward area ratio of the block is as follows:

[0118] λ f,θ =A f,θ / A s

[0119] in,

[0120] λ f,θ It is expressed as the average windward area ratio of the block under the wind direction θ, which is dimensionless;

[0121] A f,θ It is expressed as the projected area of ​​the windward side facade on the normal surface perpendicular to the wind direction, considering the wind direction θ, in m 2 , except for a few cylindrical towers, A f,θIt will vary to a certain extent with the wind direction θ;

[0122] A s It is expressed as the area of ​​the block base under the wind direction θ, in m 2 ;

[0123] Furthermore, the urban morphology analysis in step S3 includes: evaluating whether the target block is suitable for wind energy development, focusing on the evaluation of the surrounding blocks λ in the graphical and quantitative analysis. f,θ size, when the surrounding blocks λ f,θ When the overall size is small, the target block is shielded by a weaker effect and is suitable for wind energy development; when the surrounding blocks are f,θ When the overall area is large, the target block will be subject to a stronger shading effect, insufficient wind energy, and poor development suitability;

[0124] Furthermore, the urban morphological analysis in step S3 includes: when conducting statistics on the windward area ratio at the block scale, statistics on local dominant wind directions or multiple wind directions can be performed according to specific needs, such as eight wind directions and sixteen wind directions; the windward area ratio can reflect the average value of the overall situation of each block, and the windward area ratio can assist in calculating the projected area of ​​the windward side facade on the plane perpendicular to the wind direction; the windward area ratio includes: manual identification of the windward surface and rapid identification using a parametric method. For example, when a facade whose normal direction is at an obtuse angle to the wind direction is determined to be the windward surface, that is, when the wind direction θ>90°, but excluding the wind direction θ=180°, the projected area calculation formula is as follows:

[0125] A f,θ =sin(θ-90°)A f

[0126] When the wind direction θ = 180°, the facade and the wind direction are perpendicular to each other;

[0127] The urban morphology analysis in step S3 includes:

[0128] Step S301: Calculate the average windward area ratio λ of the block f and height statistics;

[0129] Step S302: Identify low shadowing effect areas at the block scale;

[0130] Step S303: Identify the weak wake impact area at the building scale;

[0131] Preferably, as shown in the attached Figure 3 As shown in the figure, the λ of the example urban area under the two wind directions of northeast by east (ENE) and southeast by south (SSE) is f Distribution, if the block's λ fWhen the value is larger, the shielding effect on the downwind blocks is stronger. In the example urban area, the blocks located south of blocks #15 and #16 and the blocks located northeast of block #04 have a λ f The λ values ​​of blocks #01 to #16 in the SSE wind direction are all high. f The overall level is higher; therefore, the entire area of ​​the example urban area is subject to a stronger shielding effect and the wind force is relatively weak;

[0132] Furthermore, as attached Figure 4 As shown, the λ of the eight blocks around each of the blocks #01 to #16 in the example urban area is f Quantitative statistics are performed, and the results of quantitative statistics are shown as follows: λ of the surrounding blocks of block #04 and blocks #14 to #16 f The overall height is relatively high and is more affected by the shading effect, so priority is given to wind energy collection in the remaining blocks.

[0133] Furthermore, as attached Figure 5 As shown in the figure, the example urban area is affected by two wind directions, namely, the northeast-east (ENE) and the southeast-southeast (SSE). There is a superimposed influence on the building wake area. The height of residential buildings in the example urban area is 18 to 100 meters, and the height of office buildings is 50 to 330 meters. In order to simplify the analysis process, the influence of the wake area of ​​buildings below 15 meters is ignored. At the same time, the red and blue gradient color bar is used to intuitively show the change of the wake effect gradually weakening with the increase of the distance from the building. Figure 5 It can be concluded that building roofs above the wake area are ideal priority locations for wind energy collection. Under the ENE wind direction, the #04 block is significantly affected by the wake effect. Whether the buildings in the remaining blocks are affected by the wake effect can be viewed one by one through the diagram.

[0134] Step S4: Let the average frontal area ratio of the block be f The graphic represents a high-suitability neighborhood;

[0135] Step S5: let the wake superimposed graphic represent the high suitability building;

[0136] Step S6: perform a rough suitability assessment;

[0137] Step S7: Determine whether accurate evaluation is required;

[0138] Furthermore, in step S7, it is determined whether a precise evaluation is required. Specifically, if the determination is yes, the process jumps to step S8; if the determination is no, the process jumps to step S9;

[0139] Step S8: performing computational fluid dynamics analysis;

[0140] Furthermore, the computational fluid dynamics analysis performed in step S8 includes:

[0141] Step S801: performing a high-resolution RANSCFD simulation, wherein the high-resolution RANSCFD simulation specifically refers to performing a computational fluid dynamics simulation based on the Reynolds-averaged Navier-Stokes equations;

[0142] Step S802: performing three-dimensional flow field analysis;

[0143] Step S803: quantifying the wind energy potential of the roof layer and representing it as a wind power density graph;

[0144] Step S804: performing accurate wind energy assessment;

[0145] Step S9: Output the result and end;

[0146] Furthermore, the high-resolution RANSCFD simulation in step S801 includes: the Reynolds-averaged Navier-Stokes model (RANS) is capable of performing CFD simulation of urban boundary layer airflow, and the considerations of the CFD simulation include: computational domain, boundary conditions, and grid method;

[0147] Preferably, taking the neutral atmospheric boundary layer velocity inlet as an example, the velocity conforms to the logarithmic function form, as shown below:

[0148] U(Z)=(u * / κ)ln((Z+Z0) / Z0)

[0149] in,

[0150] Z represents the height in meters;

[0151] U(Z) represents the wind speed in the atmospheric boundary layer at height Z, that is, the wind velocity;

[0152] u * Expressed as friction velocity in m / s;

[0153] κ is the Karman constant, for example, 0.4;

[0154] Z0 is the roughness length of the underlying surface, in meters.

[0155] Furthermore, the high-resolution RANSCFD simulation in step S801 further includes: analyzing the flow velocity distribution at the roof layer;

[0156] The analysis of the flow velocity distribution at the roof layer includes: based on the wind velocity results obtained by analysis, further calculations are performed to obtain the wind power density (PD), and then the obtained wind power density calculation results are plotted into an isovalue cloud map to intuitively display the differences in wind energy potential of different building roofs. The calculation formula is as follows:

[0157] PD=0.5ρU 3

[0158] in,

[0159] ρ is the air density in kg / m 3 ;

[0160] U represents the air velocity in m / s;

[0161] Furthermore, the high-resolution RANSCFD simulation is performed in step S801, specifically, generating a grid of appropriate accuracy based on the three-dimensional volume model of urban buildings, setting a reasonable calculation domain and boundary conditions, using the RANS model to carry out simulation analysis, and calculating the wind energy density in the post-processing step based on the obtained flow field velocity results.

[0162] For example, we analyze the changes in the frequency-weighted average wind speed under different local wind directions. The boundary condition is set to a blockage ratio of no more than 3%. The RANS model used is the Realizable k-ε model. CustomField Functions in FLUENT are used to compile the wind energy density calculation formula. The roof layer is defined as the area extending 1 to 3 meters outward from the building roof. The wind speed data at this location is extracted as the roof layer wind speed. For the ENE wind direction, 3.2m / s is used as the reference wind speed; for the SSE wind direction, 3.0m / s is used as the reference wind speed. Figure 6 As shown, the wind energy density distribution of the example urban area can intuitively understand the wind energy potential of different blocks and different building roofs. Under the ENE and SSE wind directions, blocks #01, #02 and the north block all show greater wind energy potential. In contrast, under the SSE wind direction, the overall wind energy potential of the urban area is less than that under the ENE wind direction.

[0163] The present invention provides a graphical system for evaluating the suitability of wind energy development in heterogeneous urban areas, comprising:

[0164] Module M1: Constructing a building database based on vector data;

[0165] Module M2: Rough assessment of the building database;

[0166] Module M3: Conducting urban morphological analysis;

[0167] The urban morphology analysis in the module M3 includes:

[0168] Module M301: Calculate the average frontal area ratio λ of the block f and height statistics;

[0169] Module M302: Identify low shadowing effect areas at the block scale;

[0170] Module M303: Identify weak wake impact areas at the building scale;

[0171] Module M4: Let the average frontal area ratio of the block be λ f The graphic represents a high-suitability neighborhood;

[0172] Module M5: Let the wake overlay diagram represent high suitability buildings;

[0173] Module M6: Conduct a rough suitability assessment;

[0174] Module M7: Determine whether accurate evaluation is required. If yes, jump to module M8; if no, jump to module M9;

[0175] Module M8: Perform computational fluid dynamics analysis;

[0176] The computational fluid dynamics analysis performed in the module M8 includes:

[0177] Module M801: performing high-resolution RANSCFD simulation, wherein the high-resolution RANSCFD simulation specifically refers to performing computational fluid dynamics simulation based on the Reynolds-averaged Navier-Stokes equations;

[0178] Module M802: Perform three-dimensional flow field analysis;

[0179] Module M803: Quantify the wind energy potential of the roof layer and present it as a wind power density diagram;

[0180] Module M804: Conducting accurate wind energy assessment;

[0181] Module M9: Output the results and end.

[0182] The present invention also provides a graphical heterogeneous texture urban area wind energy development suitability assessment system, which can be implemented by executing the process steps of the graphical heterogeneous texture urban area wind energy development suitability assessment method, that is, those skilled in the art can understand the graphical heterogeneous texture urban area wind energy development suitability assessment method as a preferred implementation of the graphical heterogeneous texture urban area wind energy development suitability assessment system.

[0183] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. The embodiments of this application and the features in the embodiments may be combined with each other in any manner unless there is a conflict.

Claims

1. A graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas, characterized by: include: Step S1: constructing a building database based on vector data; Step S2: perform a rough assessment of the building database; Step S3: Conduct urban morphology analysis; Step S4: Let the average frontal area ratio of the block be f The graphic represents a high-suitability neighborhood; Step S5: let the wake superimposed graphic represent the high suitability building; Step S6: perform a rough suitability assessment; Step S7: Determine whether accurate evaluation is required. If yes, jump to step S8; if no, jump to step S9; Step S8: performing computational fluid dynamics analysis; Step S9: Output the result and end.

2. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: Step S1 has low requirements for the integrity of the building volume geometric representation in the data file. The building volume geometric representation includes: open surfaces and closed volumes; the building database includes: building base outlines and height information; the building database generates a minimum rectangular volume for each building that is parallel or perpendicular to the wind direction based on a bounding box method; the leeward side facade of the minimum rectangular volume is always perpendicular to the wind direction and serves as the reference surface for drawing the wake area.

3. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: The step S1 of constructing a building database based on vector data includes: the building database draws a wake area based on the height H of each individual building, and the shape of the drawn wake area includes: an elliptical cone shape and a truncated cone shape; the truncated cone shape specifically means that when the target building is a cube or the facade perpendicular to the wind direction is a square, the wake area appears as a truncated cone; the elliptical cone shape specifically means that the top surface of the elliptical cone starts from the leeward facade of the building, with the building height and width as the two axes of the ellipse; the rotation axis of the elliptical cone starts from the center point of the leeward facade and extends outward along the normal direction of the facade, with a length of 5 to 15 times the height H; the size of the bottom surface of the elliptical cone is 1.5 to 2 times the size of the top surface.

4. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: The step S2 requires that the building be represented as a closed geometric volume and allows reasonable simplification of changes in the size of building details; further, both the steps S1 and S2 rely on an urban building database, which contains electronic vector files, including: shp, dwg, and 3dm.

5. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: The urban morphology analysis in step S3 includes: quantitative analysis of the average windward area ratio of blocks and quantitative analysis of building heights; the calculation formula for the quantitative analysis of the average windward area ratio of blocks is as follows: l f =A f / A S in, λ7 represents the average windward area ratio of the block and is dimensionless; A f Expressed as the area of ​​the windward side facade, unit is m 2 ; A S Expressed as the area of ​​the block base in m 2 ; When considering the wind direction θ on λ f When considering the impact of , the calculation formula for the quantitative analysis of the average windward area ratio of the block is as follows: l f,θ =A f,θ / A s in, λ f,θ It is expressed as the average windward area ratio of the block under the wind direction θ, which is dimensionless; A f,θ It is expressed as the projected area of ​​the windward side facade on the normal surface perpendicular to the wind direction, considering the wind direction θ, in m 2 , except for a few cylindrical towers, A f,θ It will change with the wind direction θ; A s It is expressed as the area of ​​the block base under the wind direction θ, in m 2 ; Furthermore, the urban morphology analysis in step S3 includes: evaluating whether the target block is suitable for wind energy development, focusing on the evaluation of the surrounding blocks λ in the graphical and quantitative analysis. f,θ size, when the surrounding blocks λ f,θ When the overall size is small, the target block is shielded by a weaker effect and is suitable for wind energy development; when the surrounding blocks are f,θ When the overall area is large, the target block will be subject to a stronger shading effect, insufficient wind energy, and poor development suitability.

6. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: The urban morphological analysis in step S3 includes: when conducting statistics on the windward area ratio at the block scale, statistics on the local dominant wind direction or multiple wind directions can be performed according to specific needs; the windward area ratio can reflect the average value of the overall situation of each block; the windward area ratio can assist in calculating the projected area of ​​the windward side facade on the plane perpendicular to the wind direction; the windward area ratio includes: manual identification of the windward surface, rapid identification using a parameterized method, when it is determined that the facade whose normal is at an obtuse angle to the wind direction is the windward surface, that is, when the wind direction θ>90°, but excluding the wind direction θ=180°, the calculation formula of the projected area is as follows: A f,θ =sin(θ-90°)A f When the wind direction θ=180°, the facade and the wind direction are perpendicular to each other.

7. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: The urban morphology analysis in step S3 includes: Step S301: Calculate the average windward area ratio λ of the block f and height statistics; Step S302: Identify low shadowing effect areas at the block scale; Step S303: Identify the weak wake impact area at the building scale.

8. The graphical method for evaluating the suitability of wind energy development in heterogeneous urban areas according to claim 1 is characterized in that: The computational fluid dynamics analysis performed in step S8 includes: Step S801: performing high-resolution RANSCFD simulation; Step S802: performing three-dimensional flow field analysis; Step S803: quantifying the wind energy potential of the roof layer and representing it as a wind power density graph; Step S804: performing accurate wind energy assessment; Furthermore, the high-resolution RANSCFD simulation performed in step S801 specifically refers to performing computational fluid dynamics simulation based on the Reynolds-averaged Navier-Stokes equations. The Reynolds-averaged Navier-Stokes equations model can simulate urban boundary layer airflow. Factors to consider in the urban boundary layer airflow simulation include: computational domain, boundary conditions, and grid method. When the urban boundary layer airflow simulates the neutral atmospheric boundary layer velocity, the neutral atmospheric boundary layer velocity conforms to a logarithmic function form, as shown below: U(Z)=(u * / κ)ln((Z+Z0) / Z0) in, Z represents the height in meters; U(Z) represents the wind speed in the atmospheric boundary layer at height Z, that is, the wind velocity; u * Expressed as friction velocity in m / s; κ is the Karman constant, for example, 0.4; Z0 represents the roughness length of the underlying surface, in m; Furthermore, the high-resolution RANSCFD simulation in step S801 further includes: analyzing the flow velocity distribution of the roof layer; the analyzing the flow velocity distribution of the roof layer includes: based on the wind velocity result obtained by analysis, further performing calculations to obtain wind energy density, and then plotting the obtained wind energy density calculation results into an isovalue cloud map to intuitively display the differences in wind energy potential of different building roofs. The calculation formula is as follows: PD=0.5ρU 3 in, ρ is the air density in kg / m 3 ; U represents the air velocity in m / s; Furthermore, the high-resolution RANSCFD simulation is performed in step S801, specifically, generating a grid of appropriate accuracy based on the three-dimensional volume model of urban buildings, setting a reasonable calculation domain and boundary conditions, using the RANS model to carry out simulation analysis, and calculating the wind energy density in the post-processing step based on the obtained flow field velocity results.

9. A graphical system for evaluating the suitability of wind energy development in heterogeneous urban areas, characterized by: include: Module M1: Constructing a building database based on vector data; Module M2: Rough assessment of the building database; Module M3: Conducting urban morphological analysis; Furthermore, the urban morphology analysis in the module M3 includes: Module M301: Calculate the average frontal area ratio λ of the block f and height statistics; Module M302: Identify low shadowing effect areas at the block scale; Module M303: Identify weak wake impact areas at the building scale; Module M4: Let the average frontal area ratio of the block be λ f The graphic represents a high-suitability neighborhood; Module M5: Let the wake overlay diagram represent high suitability buildings; Module M6: Conduct a rough suitability assessment; Module M7: Determine whether a precise assessment is needed; Module M8: Perform computational fluid dynamics analysis; Furthermore, the computational fluid dynamics analysis performed in the module M8 includes: Module M801: performing high-resolution RANSCFD simulation, wherein the high-resolution RANSCFD simulation specifically refers to performing computational fluid dynamics simulation based on the Reynolds-averaged Navier-Stokes equations; Module M802: Perform three-dimensional flow field analysis; Module M803: Quantify the wind energy potential of the roof layer and present it as a wind power density diagram; Module M804: Conducting accurate wind energy assessment; Module M9: Output the results and end.

10. A graphical device for evaluating the suitability of wind energy development in heterogeneous urban areas, characterized in that: By adopting the method of the graphical heterogeneous texture urban area wind energy development suitability assessment system described in any one of claims 1 to 8, the graphical distribution of wind energy potential is achieved through the heterogeneous texture urban area wind energy development suitability assessment.

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