Building external sunshade dynamic photo-thermal regulation and control optimization method and system based on joint simulation

Abstract

The invention provides a building external sunshade dynamic photo-thermal regulation and control optimization method and system based on joint simulation, and relates to the technical field of building design, and the method comprises the steps: building a building model, and setting building operation parameters; constructing an external shading calculation model of the building; simulating and calculating energy consumption intensity, sunlight utilization indexes and glare probabilities under different external sunshade regulation and control thresholds according to historical meteorological data on the basis of the constructed building model and the external sunshade calculation model; and performing multi-objective optimization on the obtained energy consumption intensity, sunlight utilization index and glare probability under different external sunshade regulation and control thresholds, and determining an optimal external sunshade regulation and control threshold. The optimal external sunshade opening threshold value can be screened, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of building design, and in particular to a method and system for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation. Background Art

[0002] The external shading control threshold refers to the standard for the automatic opening of external shading equipment (such as blinds, sunshades, etc.) under specific environmental conditions (such as when the solar radiation intensity or outdoor temperature reaches a certain set value). The external shading control threshold has an important impact on the lighting and air-conditioning energy consumption of the building. When the external shading control threshold is set too high, although the lighting demand and energy consumption are reduced, more solar radiation enters the room, which will increase the air-conditioning energy consumption and may cause an increase in glare and illumination. On the contrary, if the threshold is set too low, although the solar radiation entering the room and the air-conditioning energy consumption can be reduced, the lighting demand and energy consumption will increase, and the glare and illumination will also decrease. In the related art, the external shading control threshold is usually determined from a single energy consumption perspective with the goal of minimum energy consumption. However, this method only focuses on a single performance indicator and ignores the influence of other factors, resulting in the shading effect not being able to meet the user's visual comfort and other needs, affecting the user experience. Summary of the invention

[0003] In order to address the deficiencies of the prior art, the purpose of the present invention is to provide a method and system for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation, so as to screen the optimal exterior shading opening threshold and achieve multi-dimensional optimization of energy efficiency, lighting efficiency and visual comfort.

[0004] In order to achieve the above objectives, according to some embodiments, a first aspect of the present invention provides a method for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation, comprising:

[0005] Build building models and set building operation parameters;

[0006] Construct a calculation model for the building's external shading;

[0007] Based on the constructed building model and external shading calculation model, and according to historical meteorological data, the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds are simulated and calculated;

[0008] Multi-objective optimization is performed on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds to determine the optimal external shading control threshold.

[0009] According to a further technical solution, the building model comprises an exterior window model and a building geometry model.

[0010] A further technical solution is that the building operation parameters include the number of people in the building, lighting and equipment load power, air conditioning parameters and the schedule of various activities in the building.

[0011] A further technical solution also includes setting a natural light illumination measurement point at a set position in the building according to the purpose of the building, and setting a corresponding illumination standard value; when the illumination at the natural light illumination measurement point is lower than the corresponding illumination standard value, turning on artificial lighting.

[0012] A further technical solution is that the external shading calculation model includes the form, photothermal performance and installation position of the external shading device.

[0013] Further technical solutions, based on entropy weight method and TOPSIS method for multi-objective optimization, include:

[0014] Based on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds, an evaluation matrix is ​​constructed and data preprocessing is performed;

[0015] Calculate the information entropy of each indicator and determine the weight of each indicator based on the information entropy;

[0016] Construct a weighted normalization matrix and determine the ideal solution and the negative ideal solution;

[0017] Calculate the Euclidean distance and calculate the normalized score of each solution;

[0018] The optimal external shading control threshold is determined based on the normalized score.

[0019] The second aspect of the present invention provides a building exterior shading dynamic light and heat control optimization system based on joint simulation, comprising:

[0020] A building model building module is configured to build a building model and set building operation parameters;

[0021] The external shading calculation model building module is configured to build an external shading calculation model of the building;

[0022] The calculation module is configured to simulate and calculate the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds based on the constructed building model and external shading calculation model and according to historical meteorological data;

[0023] The multi-objective optimization module is configured to perform multi-objective optimization on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds to determine the optimal external shading control threshold.

[0024] A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the above-mentioned method for optimizing dynamic light and heat regulation of exterior building shading based on joint simulation.

[0025] In a fourth aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions. When the computer instructions are executed by a processor, the steps of the above-mentioned method for optimizing dynamic light and heat regulation of exterior building shading based on joint simulation are completed.

[0026] A fifth aspect of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention provides a method and system for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation. By performing multi-objective optimization on three indicators, namely, glare probability (DGP), daylight utilization index (UDI) and energy consumption intensity (EUI), the optimal external shading regulation threshold is determined. Compared with the prior art, this method solves the defect that the traditional method only focuses on a certain performance indicator. By comprehensively optimizing DGP, UDI and EUI, a comprehensive improvement in comfort, lighting efficiency and energy efficiency is achieved, and the user experience is improved. Specifically, optimizing DGP reduces glare and improves visual comfort; optimizing UDI reduces dependence on artificial lighting and improves natural lighting; optimizing EUI reduces building energy consumption.

[0029] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0031] Figure 1 is a schematic diagram of the method of the present invention;

[0032] Figure 2 is a schematic diagram of the performance parameters of the exterior window of the present invention;

[0033] Figure 3 A schematic diagram of modeling a building geometric model of the present invention;

[0034] Figure 4It is a dotted line schematic diagram of the multi-objective optimization result of the present invention. DETAILED DESCRIPTION

[0035] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0036] Embodiment 1

[0037] Embodiment 1 of the present invention, as Figure 1-Figure 4 As shown, a method for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation is provided, including:

[0038] S1. Build a building model and set building operation parameters;

[0039] S2. Construct the external shading calculation model of the building;

[0040] S3. Based on the constructed building model and external shading calculation model, according to historical meteorological data, simulate and calculate the energy intensity EUI index, daylight utilization index UDI index and glare probability DGP index under different external shading control thresholds;

[0041] S4. Perform multi-objective optimization on the energy consumption intensity EUI index, daylight utilization index UDI index and glare probability DGP index under different external shading control thresholds to determine the optimal external shading control threshold.

[0042] In step S1, the building model includes an exterior window model and a building geometry model. The exterior window model is constructed based on the actual exterior window structure of the building. In this embodiment, the exterior window model is established using Window software, which can calculate the light and heat performance of windows (U value, solar heat gain coefficient, visible light transmittance, etc.). The software has a built-in glass performance database, and the window model can be selected and constructed according to actual needs.

[0043] Create a geometric model of the exterior window, select the glass type that matches the actual window, and set the corresponding light and heat performance data according to the window material, thickness, coating and other parameters. Use this model to calculate the light and heat transfer characteristics of the exterior window and obtain data including window heat transfer coefficient, solar energy transmittance, etc. Export these light and heat data together with the exterior window model to generate an IDF file suitable for EnergyPlus for subsequent building energy efficiency simulation.

[0044] The building geometry model is established according to the basic profile and design requirements of the building. In this embodiment, the building geometry model is constructed using SketchUp software. SketchUp is an easy-to-use 3D modeling software that is widely used in architectural design, interior design, and urban planning. It is known for its intuitive interface and flexible modeling tools. The Openstudio plug-in is an extension tool for SketchUp, specifically for building energy consumption simulation and analysis. By combining the Openstudio plug-in, users can create and edit building models in SketchUp, and import them into energy consumption simulation software for calculation, thereby optimizing building design.

[0045] Based on basic parameters such as building orientation, floor area, length, width and height, building form, and window-to-wall ratio, the building facade and internal partitions are modeled. According to the needs of different rooms and functional areas, the building space is divided into multiple simulated thermal zones to facilitate more accurate load and energy efficiency analysis. Based on the OpenStudio plug-in, the established building model is integrated with its thermal zone allocation information, and the building geometry model IDF file for EnergyPlus is exported for subsequent energy efficiency simulation.

[0046] Integrate the exterior window model and the building geometry model. In this embodiment, based on the EnergyPlus software, the exported exterior window model IDF file is integrated with the building geometry model IDF file. EnergyPlus is a building energy consumption simulation software that can not only simulate data such as outdoor temperature, outdoor solar radiation, and solar radiation on the building surface, but also simulate and output data such as building load, air conditioning system energy consumption, and lighting energy consumption based on the built-in building performance optimization module and calculation model.

[0047] By importing the light and heat data and construction information of the exterior windows, ensure that the exterior windows accurately reflect their heat transfer and solar energy transmission performance in the building energy efficiency simulation. Input the detailed construction and performance parameters of the building envelope (such as walls, roofs, floors, etc.), including the thermal conductivity, thickness, density and other data of the materials, to ensure that the thermal performance of the building envelope is correctly simulated.

[0048] Input of building operation design parameters. Based on EnergyPlus software, set the building operation parameters, including the number of people in the building, lighting and equipment load power, air conditioning parameters (type and operation mode of air conditioning system), and the schedule of various activities in the building. According to the usage of different functional areas, input the number of people and activity frequency, set the power load of lighting and equipment, and define the operation time and control strategy of the air conditioning system. By reasonably configuring these parameters, ensure that the energy efficiency simulation of the building can reflect the energy consumption characteristics in actual use.

[0049] In addition, step S1 also includes constructing a lighting energy-saving calculation model. Based on the EnergyPlus software, through the Daylighting: ReferencePoint module, the natural light illumination measurement points and their positions in each area are set according to the specific purpose and functional requirements of the building. Each measuring point sets the corresponding illumination standard value according to the use nature and design requirements of the room, and defines the control area, that is, the influence range of natural light in the area. Through the Daylighting: Controls module, these measuring points are integrated to set the natural light calculation method and lighting energy-saving control strategy. When the natural light illumination of the measuring point is lower than the illumination standard value, artificial lighting is automatically turned on to meet the indoor lighting needs.

[0050] In step S2, the external shading calculation model can be constructed using the EnergyPlus software. In the EnergyPlus software, select the external shading form to be installed, such as roller blinds, shutters, etc., and enter the corresponding light and thermal performance of the external shading equipment (such as solar radiation transmittance, solar radiation reflectance, visible light transmittance, visible light reflectance, thickness, thermal conductivity) and installation location. Through the built-in WindowShadingControl module, select the use area of ​​the external shading equipment, and set the control method, such as control based on the intensity of solar radiation incident on the surface of the external window, and set an opening threshold in each use area. Set the range of different control thresholds to establish a comparison model of multiple groups of external shading control thresholds.

[0051] In step S3, historical meteorological data adopts meteorological year data in the past set time period of the region. In this embodiment, the typical meteorological year data is based on the monthly average of the past 30 years, and the month closest to the 30-year average is selected from the meteorological data of the past 10 years as the representative of the typical meteorological year. The data source adopts the CSWD data source, and the data format is EPW. The meteorological file provides key information for simulation, including meteorological data such as outdoor temperature, vertical direct solar radiation, and vertical scattered solar radiation.

[0052] Based on the established model and input conditions and data, building energy consumption simulation, building glare simulation and illumination simulation are carried out.

[0053] The energy consumption of building lighting and air conditioning is simulated based on the calculation program of EnergyPlus software. The simulation is performed according to the range of different control thresholds set in step S2, and the simulation results will be output in the form of a CSV table, including detailed lighting energy consumption and air conditioning energy consumption data. The building energy intensity EUI is calculated based on the simulation results to provide data support for evaluating building energy efficiency and optimizing design.

[0054] Building glare simulation and illumination simulation can be performed based on Radiance software. Import the building model built with SketchUp software into Radiance software, and integrate the window optical property data exported from Window software. Use the gendaylit tool of Radiance software to import standard meteorological year data, and define the properties of each surface material for the building model, including reflectivity and optical property parameters. Set up a sensor network at key locations of the building, calculate the illumination value of each measuring point through the rtrace command, and then derive the daylight utilization index UDI indicator for evaluating the natural lighting effect. At the same time, use the evalglare tool to calculate the daylight glare probability DGP indicator in the building to evaluate the glare impact.

[0055] In step S4, the Rhino&Grasshopper platform calls the simulation data, and uses the Rhino&Grasshopper platform to call the energy consumption EUI index obtained by the EnergyPlus simulation and the illuminance UDI and glare DGP index obtained by the Radiance software simulation.

[0056] For the obtained simulation data, the multi-objective optimization of energy consumption, glare and illumination is carried out based on the entropy weight method, and the optimal control threshold is screened: the entropy weight method is used to optimize the three objectives of EUI, UDI and DGP. First, the evaluation matrix is ​​constructed and the data is preprocessed to calculate the information entropy of each indicator; then the TOPSIS method is used to construct a standardized weighted matrix, determine the ideal solution and the negative ideal solution, calculate the Euclidean distance and obtain the normalized score of each scheme; finally, the schemes with different external shading control thresholds are sorted according to the scores, the optimal scheme is screened, the optimal external shading control threshold is determined, and the final multi-objective optimal scheme is obtained, covering the lighting and air conditioning energy consumption EUI, illumination UDI and glare DGP indicators.

[0057] Specifically, an m×n evaluation matrix is ​​constructed, where m is the number of schemes, each scheme corresponds to a different external shading control threshold, and n is the number of indicators, which is 3 here (EUI, UDI, DGP). Since each indicator has a different dimension, the data needs to be standardized to ensure the fairness of the comparison.

[0058] Then calculate the information entropy. For each indicator, calculate its probability distribution in all scenarios. Using the formula To calculate the information entropy of the jth index, where p ij is the probability of the i-th option on the j-th indicator, is a constant. The weight of each indicator is calculated based on the information entropy. The smaller the information entropy, the more information it provides and the greater the corresponding weight.

[0059] A standardized weighted matrix is ​​constructed, and the calculated weights are applied to the standardized evaluation matrix to construct a weighted standardized matrix.

[0060] For the ideal solution, the benefit-type indicators (such as UDI) take the maximum value, and the cost-type indicators (such as EUI, DGP) take the minimum value.

[0061] For the negative ideal solution, contrary to the ideal solution, the benefit-type indicators (such as UDI) take the minimum value and the cost-type indicators (such as EUI, DGP) take the maximum value.

[0062] Calculate the Euclidean distance of each solution to the ideal solution and the negative ideal solution respectively, denoted as and

[0063] Calculate the normalized score of each solution based on the Euclidean distance: C i The value of is between 0 and 1. The closer to 1, the better the scheme. Finally, different schemes, that is, schemes with different shading control thresholds, are ranked according to the normalized score to determine the optimal external shading control threshold.

[0064] This embodiment determines the optimal external shading control threshold by performing multi-objective optimization on the three indicators of DGP (glare probability), UDI (daylight utilization index) and EUI (energy consumption intensity). Compared with the prior art, this solves the problem of traditional methods focusing on a single performance indicator. Traditional methods often ignore the impact of other performance indicators, which may lead to a decrease in the overall effect. However, this embodiment achieves a comprehensive improvement in comfort, lighting efficiency and energy efficiency by comprehensively optimizing DGP, UDI and EUI. Specifically, optimizing DGP reduces glare and improves visual comfort; optimizing UDI reduces dependence on artificial lighting and improves natural lighting; optimizing EUI reduces building energy consumption. At the same time, the present invention allows designers to flexibly adjust design plans, enhance the adaptability and flexibility of the design, and solves the deficiency of traditional methods that lack multi-dimensional evaluation support.

[0065] At the same time, this embodiment uses the Rhino&Grasshopper platform to integrate EnergyPlus and Radiance software, and through parametric modeling and design, it realizes seamless data export and import, improves the efficiency of multi-platform collaboration, supports real-time design adjustment, and evaluates the impact of shading equipment on indoor natural lighting and energy consumption. In addition, the multi-objective optimization algorithm can find the best balance between natural lighting and energy consumption, and optimize the performance of building design. The automated performance evaluation module combines parametric models and optimization algorithms to quickly evaluate the performance of different design schemes in terms of lighting and energy consumption, and supports design iteration and decision-making. This method has the advantages of scientificity, high efficiency, visualization and quantification, and provides an innovative solution for achieving efficient, comfortable and environmentally friendly building design.

[0066] Embodiment 2

[0067] This embodiment provides a building exterior shading dynamic light and heat control optimization system based on joint simulation, including:

[0068] A building model building module is configured to build a building model and set building operation parameters;

[0069] The external shading calculation model building module is configured to build an external shading calculation model of the building;

[0070] The calculation module is configured to simulate and calculate the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds based on the constructed building model and external shading calculation model and according to historical meteorological data;

[0071] The multi-objective optimization module is configured to perform multi-objective optimization on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds to determine the optimal external shading control threshold.

[0072] It should be noted here that the various modules in this embodiment correspond one-to-one to the steps of the method in Example 1, and the specific implementation process is the same, which will not be repeated here.

[0073] Embodiment 3

[0074] This embodiment selects real parameters in an actual scenario and performs simulation using the method in the first embodiment to verify the effectiveness of the method in the first embodiment.

[0075] Build and export the model based on the actual exterior window: Based on the window software, a double-layer Low-E glass model is established. The parameters of the inner and outer glass layers and the light and heat performance parameters of the entire window are as follows: Figure 2 As shown, and export the idf file.

[0076] Typical building model establishment: Figure 3 As shown in the figure, based on SketchUp software, a geometric model of a typical office was established, with a size of 6×5×3m (6m on the south side), and a 4.5×2m external window with a window sill height of 0.75m on the south side of the building. The optimization team divided the model into a hot zone and used the OpenStudio plug-in to export the idf file.

[0077] Integrate the building and exterior window models: Based on EnergyPlus software, integrate the idf files of the exterior window and building models and input them into Figure 2 Calculated glass parameters; the heat transfer coefficient of the roof is set to 0.4W / m 2 K, the heat transfer coefficient of the wall is set to 1.5W / m 2K, the heat transfer coefficient of the floor is set to 2W / m 2 ·K.

[0078] Building operation design parameter input: According to the actual office operation status, the number of people is set to 6 and the lighting power is set to 8W / m 2 , the power of other equipment is set to 13W / m 2 The illumination target is set at 500lx, the COP value of the summer air-conditioning chiller is 5.3, the summer air-conditioning temperature is 26℃, and the use time of indoor air-conditioning and outdoor shading equipment is set from 5:00 am to 22:00 pm.

[0079] Construction of lighting energy-saving calculation model: set a 0.75m high illuminance measurement point in the center of the room, and set the natural light calculation method to SplitFlux to accurately calculate the natural lighting illuminance in the room; at the same time, set the lighting energy-saving method to ContinuousOff, so that artificial lighting is turned off after the target illuminance is reached, and turn on the corresponding lighting to supplement the artificial lighting demand if the illuminance requirement is not met.

[0080] External shading calculation model construction: set up external sunshade roller blinds on the south-facing windows of the room, with the following parameters: solar radiation transmittance 0.05, solar radiation reflectance 0.85, visible light transmittance 0.05, visible light reflectance 0.85, thickness 0.005m, thermal conductivity 0.1W / m·K, and the distance between the external roller blinds and the window is 0.05m. At the same time, set up external sunshade roller blinds based on the intensity of solar radiation incident on the surface of the external window, and the control thresholds are set to 50, 100, 150, 200 and 250W / m 2 , in order to find the optimal control threshold.

[0081] Importing standard meteorological year data: Importing standard meteorological year data of a city in a hot summer and warm winter area. In this embodiment, a summer design day is selected for simulation.

[0082] Typical building energy consumption simulation: Based on the above input conditions, the EnergyPlus software is used to calculate the comprehensive energy consumption EUI index of the office, including lighting and air conditioning energy consumption, under different control thresholds. For example, when the external shading control threshold is 50W / m 2 At 9:00 pm, the office had the lowest comprehensive energy consumption of 18.15 kWh, of which lighting energy consumption was 2.48 kWh and air conditioning energy consumption was 15.67 kWh.

[0083] Radiance software simulates typical building glare and illumination: input the above setting conditions (external windows, wall performance, operation schedule, roller blind parameters, external shading control threshold, etc.) into Radiance software to calculate the daylight utilization index UDI and glare probability DGP index of the office under different solar radiation external shading control thresholds. 2 When the UDI index is up to 1862.3lx, the external shading control threshold is 50W / m 2 When , the DGP glare probability index is as low as 0.152.

[0084] Rhino&Grasshopper platform calls simulation data: Using the Rhino&Grasshopper platform, the energy consumption EUI index obtained by EnergyPlus simulation and the illuminance UDI and glare DGP indexes obtained by Radiance software simulation are integrated for multi-objective optimization.

[0085] Based on the entropy weight method, multi-objective optimization of lighting and air conditioning energy consumption, glare and illumination is performed to screen the optimal control threshold: multi-objective optimization is performed on the energy consumption index EUI, daylight utilization index UDI and glare probability DGP index. The comprehensive score results of multi-objective optimization by TOPSIS method are as follows: Figure 4 As shown in Figure 2, when the external shading control threshold is 200W / m 2 When , the multi-objectives are optimal, which is the best control threshold, and its comprehensive score is 0.2484.

[0086] Embodiment 4

[0087] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method in the first embodiment.

[0088] The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor may be implemented in at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and LA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0089] The memory may include one or more computer-readable media, which may be non-transitory. The memory may also include high-speed random access memory, and non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable medium in the memory is used to store at least one computer program, which is used to be executed by the processor to implement a method for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation provided in an embodiment of the present disclosure.

[0090] Those skilled in the art can understand that the electronic device provided in this embodiment can include more or fewer components, or combine certain components, or adopt different component arrangements.

[0091] Embodiment 5

[0092] This embodiment provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the steps of the method in the first embodiment are completed.

[0093] Embodiment 6

[0094] This embodiment provides a computer program product, including a computer program / instruction, which implements the steps of the method in Embodiment 1 when executed by a processor.

[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing dynamic light and heat regulation of building exterior shading based on joint simulation, characterized in that: include: Build building models and set building operation parameters; Construct a calculation model for the building's external shading; Based on the constructed building model and external shading calculation model, and according to historical meteorological data, the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds are simulated and calculated; Multi-objective optimization is performed on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds to determine the optimal external shading control threshold.

2. The method for optimizing the dynamic light and heat regulation of building exterior shading based on joint simulation as claimed in claim 1, characterized in that: The building model includes an exterior window model and a building geometry model.

3. The method for optimizing the dynamic light and heat regulation of building exterior shading based on joint simulation as claimed in claim 1, characterized in that: The building operation parameters include the number of people in the building, lighting and equipment load power, air conditioning parameters, and schedules of various activities in the building.

4. The method for optimizing the dynamic light and heat regulation of building exterior shading based on joint simulation as claimed in claim 1, characterized in that: It also includes setting a natural light illumination measurement point at a set position in the building according to the purpose of the building, and setting a corresponding illumination standard value; when the illumination at the natural light illumination measurement point is lower than the corresponding illumination standard value, turning on artificial lighting.

5. The method for optimizing the dynamic light and heat regulation of building exterior shading based on joint simulation as claimed in claim 1, characterized in that: The external shading calculation model includes the form, light and heat performance and installation position of the external shading device.

6. The method for optimizing the dynamic light and heat regulation of building exterior shading based on joint simulation as claimed in claim 1, characterized in that: Multi-objective optimization based on entropy weight method and TOPSIS method, including: Based on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds, an evaluation matrix is ​​constructed and data preprocessing is performed; Calculate the information entropy of each indicator and determine the weight of each indicator based on the information entropy; Construct a weighted normalization matrix and determine the ideal solution and the negative ideal solution; Calculate the Euclidean distance and calculate the normalized score of each solution; The optimal external shading control threshold is determined based on the normalized score.

7. A building exterior shading dynamic light and heat control optimization system based on joint simulation, characterized in that: include: A building model building module is configured to build a building model and set building operation parameters; The external shading calculation model building module is configured to build an external shading calculation model of the building; The calculation module is configured to simulate and calculate the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds based on the constructed building model and external shading calculation model and according to historical meteorological data; The multi-objective optimization module is configured to perform multi-objective optimization on the energy consumption intensity, daylight utilization index and glare probability under different external shading control thresholds to determine the optimal external shading control threshold.

8. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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