Intelligent layout method and system for building energy consumption equipment

Abstract

The invention discloses a building energy consumption equipment intelligent layout method and system, and relates to the field of building energy consumption equipment layout. Specifically, each group of virtual scene training data comprises building scene information of each virtual building scene, equipment information of multiple pieces of building energy consumption equipment in each virtual building scene, and building energy consumption equipment layout data; defining a comprehensive reward function based on the energy efficiency function, the spatial distribution function, the equipment maintenance function and the spatial illumination function of the virtual building scene; selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model through the multiple groups of virtual scene training data, and optimizing the initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model; and obtaining a layout scheme of the to-be-tested scene data through the virtual scene training model. According to the method, an ideal layout effect can be achieved in a complicated and changeable building environment, and the design efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of layout of building energy equipment, and in particular to an intelligent layout method and system of building energy equipment. Background Art

[0002] In modern building design, the reasonable layout and positioning of building energy equipment (such as ventilation systems, air-conditioning systems, lighting equipment, and power distribution systems, etc.) are crucial and directly affect the energy efficiency and living comfort of the building. Traditional design methods rely on the experience and manual operation of designers, which is not only time-consuming and labor-intensive, but also inefficient in design, and prone to design errors and unreasonable layouts. At present, the use of intelligent algorithms to automatically layout and position building energy equipment has become a research hotspot. However, when faced with complex and changeable building environments, existing algorithms often find it difficult to achieve ideal layout effects, resulting in low design efficiency and difficulty in meeting actual needs. Therefore, at present, there is a need for an intelligent layout method and system for building energy equipment that can meet the actual complex needs of building energy equipment layout, achieve ideal layout effects, and improve design efficiency. Summary of the invention

[0003] The technical problem to be solved by the present invention is that it is difficult to achieve an ideal layout effect when facing a complex and changeable building environment, resulting in low design efficiency. The purpose is to provide an intelligent layout method and system for building energy equipment to solve the above technical problem.

[0004] The present invention is achieved through the following technical solutions:

[0005] A method for intelligent layout of building energy equipment, comprising:

[0006] Collect multiple sets of virtual scene training data according to multiple virtual building scenes; each set of the virtual scene training data includes building scene information of each virtual building scene, equipment information of multiple building energy-using equipment in each virtual building scene, and building energy-using equipment layout data;

[0007] Defining a comprehensive reward function based on the energy efficiency function, spatial distribution function, equipment maintenance function, space utilization function and spatial illumination function of the virtual building scene;

[0008] Selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model using multiple sets of the virtual scene training data, and optimizing the trained initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model;

[0009] The layout plan of the scene data to be tested is obtained through the virtual scene training model to layout the building energy equipment.

[0010] The building energy equipment layout data includes the orientation, position and connection type between each building energy equipment and the corresponding virtual building scene; the connection type includes the number of connections, connector specifications, distributable space and fixing method.

[0011] Obtaining actual production capacity and actual power consumption through equipment information of each of the energy-using equipment in the building; defining an actual energy efficiency objective function of each of the energy-using equipment in the building according to the ratio of the actual production capacity and actual power consumption of each of the energy-using equipment in the building; and obtaining the optimal actual energy efficiency by maximizing the actual energy efficiency objective function;

[0012] The type weights are analyzed through the building energy equipment layout data of multiple building energy equipment; the equipment weights are calculated according to the type weights and the actual power consumption; and the energy efficiency function of the virtual scene training model is obtained according to the optimal actual energy efficiency and equipment weight of each building energy equipment.

[0013] The analyzing type weights through the building energy equipment layout data of the plurality of building energy equipments comprises:

[0014] The equipment type of each of the building energy equipment is obtained through the equipment information of multiple building energy equipment; one or more of the orientation, position and connection type are scored according to the preset scoring rules of the equipment type of each of the building energy equipment, and the type weight of the building energy equipment is obtained according to the scoring results.

[0015] The spatial distribution function is obtained through the following steps: obtaining the equipment coverage area of ​​each of the building energy equipment through the equipment information of multiple building energy equipment; obtaining the distribution distance between different building energy equipment through the layout of multiple building energy equipment; defining a spatial distribution weight objective function for evaluating the spatial distribution weight of each building energy equipment according to the equipment coverage area of ​​each of the building energy equipment and the distribution distance between different building energy equipment; calculating the optimal spatial distribution weight using the spatial distribution weight objective function, and obtaining the spatial distribution function of the virtual scene training model according to the optimal spatial distribution weight.

[0016] The equipment maintenance function is obtained through the following steps: obtaining the installation position of each of the building energy equipment through the layout of multiple building energy equipment; obtaining the occupied space of each of the building energy equipment through the equipment information of multiple building energy equipment; defining an equipment maintenance difficulty objective function for evaluating the difficulty of equipment maintenance based on the installation position and occupied space between each of the building energy equipment; obtaining the optimal equipment maintenance difficulty using the equipment maintenance difficulty objective function, and obtaining the equipment maintenance function of the virtual scene training model based on the optimal equipment maintenance difficulty.

[0017] The space utilization function is obtained through the following steps: obtaining the installation position of each of the building energy equipment through the layout of multiple building energy equipment; obtaining the occupied space of each of the building energy equipment through the equipment information of multiple building energy equipment; defining an equipment space utilization objective function for evaluating the space utilization of each of the building energy equipment according to the ratio of the occupied space of each of the building energy equipment and the space of the corresponding virtual building scene; obtaining the optimal space utilization using the equipment space utilization objective function, and obtaining the space utilization function of the virtual scene training model according to the optimal space utilization.

[0018] The spatial illumination function is obtained through the following steps: the building energy equipment includes one or more lighting devices; according to the rated luminous flux and the lighting area of ​​each lighting device, the spatial illumination function of each lighting device is obtained corresponding to the preset standard illumination of the virtual building scene.

[0019] The building scene information of each of the virtual building scenes includes: building space information and building scene type; the equipment information of multiple building energy-using equipment includes: any one or more of size, shape, quantity, installation method, accessory specifications and operating parameters.

[0020] An intelligent layout system for building energy equipment, comprising:

[0021] The training data acquisition module is used to collect multiple sets of virtual scene training data according to multiple virtual building scenes; each set of the virtual scene training data includes the building scene information of each virtual building scene, the equipment information of multiple building energy-using equipment in each virtual building scene, and the layout data of the building energy-using equipment;

[0022] A reward function definition module: used to define a comprehensive reward function based on the energy efficiency function, spatial distribution function, equipment maintenance function, space utilization function and spatial illumination function of the virtual building scene;

[0023] A scene model training module: used for selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model through multiple sets of virtual scene training data, and optimizing the trained initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model;

[0024] Equipment scheme layout module: used to obtain the layout scheme of the scene data to be tested through the virtual scene training model to layout the building energy equipment.

[0025] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0026] The present invention provides an intelligent layout method for building energy equipment. According to multiple virtual building scenes, building scene information, multiple building energy equipment, the performance of multiple building energy equipment and the layout mode of multiple building energy equipment are respectively collected, and a virtual scene training model for the scene layout of building energy equipment is trained, so as to output the layout mode of multiple building energy equipment of the virtual scene data to be tested; and the virtual scene training model is optimized by using the comprehensive reward function defined by the energy efficiency function, spatial distribution function, equipment maintenance function and spatial illumination function of the virtual building scene; the layout scheme of the scene data to be tested is obtained by the optimized virtual scene training model, so that the model can quickly and accurately obtain the layout of building energy equipment that better meets the actual needs of the scene. The present invention solves the problem that it is difficult to achieve an ideal layout effect when facing a complex and changeable building environment, resulting in low design efficiency and difficulty in meeting actual needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0028] In the figure:

[0029] Figure 1 This is a flow chart of a method for intelligent layout of building energy equipment in Example 1 of the present invention;

[0030] Figure 2 This is a schematic diagram of the intelligent layout system of building energy equipment according to Example 2 of the present invention. DETAILED DESCRIPTION

[0031] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0032] Example 1

[0033] like Figure 1 As shown, the embodiment of the present application provides a method for intelligent layout of building energy equipment, including:

[0034] Collect multiple sets of virtual scene training data according to multiple virtual building scenes; each set of the virtual scene training data includes building scene information of each virtual building scene, equipment information of multiple building energy-using equipment in each virtual building scene, and building energy-using equipment layout data;

[0035] Defining a comprehensive reward function based on the energy efficiency function, spatial distribution function, equipment maintenance function, space utilization function and spatial illumination function of the virtual building scene;

[0036] Selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model using multiple sets of the virtual scene training data, and optimizing the trained initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model;

[0037] The layout plan of the scene data to be tested is obtained through the virtual scene training model to layout the building energy equipment.

[0038] The building scene information of each of the virtual building scenes includes: building space information and building scene type; the equipment information of multiple building energy-using equipment includes: any one or more of size, shape, quantity, installation method, accessory specifications and operating parameters.

[0039] Multiple virtual building scenes that collect multiple sets of virtual scene training data can be created for different user terminals through Revit software, including parametric families of various building virtual scenes and equipment information and equipment layout data of different building energy-using equipment.

[0040] Building energy equipment such as ventilation systems, air conditioning systems, lighting equipment, power distribution systems, etc.; equipment information includes information such as the size, shape and performance parameters of the equipment. Building energy equipment layout data includes the orientation, position and connection type between each of the building energy equipment and the corresponding virtual building scene. The connection type includes the number of connections, connector specifications, distributable space, fixing method, etc. For example: the connection type of the air conditioning system includes the number of connections (number of air outlets), connector specifications (duct size), distributable space (installation position restrictions caused by equipment characteristics), fixing method (hanging air conditioners are fixed with perforated brackets, and cabinet air conditioners are placed on the ground and fixed), etc.

[0041] The building energy equipment layout data includes the orientation, position and connection type between each building energy equipment and the corresponding virtual building scene; the connection type includes the number of connections, connector specifications, distributable space and fixing method.

[0042] Building space information may include building geometry information and building environment information; building geometry information may include the length, width, height and area of ​​one or more rooms in the building, the relative positions between different rooms, the positions of walls and doors and windows, etc. Building environment information may include building location, building orientation, weather, outdoor brightness and air visibility, etc. Virtual building scenes may be classified according to whether the living functions are the same, such as residential, office, entertainment and other types; they may also be classified according to room types, such as living room, bedroom, office, conference room and other types. Multiple building energy-using equipment may include ventilation systems, air conditioning systems, lighting equipment and power distribution systems, etc. The above-mentioned accessory specifications may include the size, quantity, installation location and installation method of the accessories, etc.

[0043] The energy efficiency function is obtained by the following steps:

[0044] Obtaining actual production capacity and actual power consumption through equipment information of each of the energy-using equipment in the building; defining an actual energy efficiency objective function of each of the energy-using equipment in the building according to the ratio of the actual production capacity and actual power consumption of each of the energy-using equipment in the building; and obtaining the optimal actual energy efficiency by maximizing the actual energy efficiency objective function;

[0045] The type weights are analyzed through the building energy equipment layout data of multiple building energy equipment; the equipment weights are calculated according to the type weights and the actual power consumption; and the energy efficiency function of the virtual scene training model is obtained according to the optimal actual energy efficiency and equipment weight of each building energy equipment.

[0046] The analyzing type weights through the building energy equipment layout data of the plurality of building energy equipments comprises:

[0047] The equipment type of each of the building energy equipment is obtained through the equipment information of multiple building energy equipment; one or more of the orientation, position and connection type are scored according to the preset scoring rules of the equipment type of each of the building energy equipment, and the type weight of the building energy equipment is obtained according to the scoring results.

[0048] The performance of the plurality of building energy-using equipment includes the model, equipment name and equipment purpose, etc., which are used to distinguish the equipment type. The equipment type can be identified. Then, according to the scoring rule of the type, one or more corresponding data in the building energy-using equipment layout data are scored, so that the type weight is calculated according to the score size. The type scoring can adopt the following rules:

[0049] For example, the 10-point scoring mechanism for each performance parameter can be set as follows: 10 points means full compliance with the requirements; 7-9 points means basically compliance with the requirements; 4-6 points means partial compliance with the requirements; 1-3 points means serious non-compliance with the requirements; the above specific judgment criteria can be adjusted with reference to the relevant technical standards of the equipment type. Taking cabinet air conditioner A as an example, the following parameters can be selected to evaluate the equipment type weight: the number of air outlets is 4 (8 points), the diameter of the air duct is 100mm (9 points), it can be distributed in the two corners of the living room by the window (6 points), and the fixing method is directly placed on the ground (6 points). The comprehensive score is 29 points. The above scoring system is only used as an example, and it can be scored manually. When a large number of building energy-using equipment needs to be scored, the actual impact of various parameters on energy efficiency can be verified based on a large amount of experimental data of the relevant equipment type, so as to obtain the corresponding type weight value.

[0050] Optionally, the type scores of multiple building energy-using equipment of the same equipment type in the current virtual building scene are normalized and the type weights are obtained by comprehensive calculation, which can be expressed as:

[0051]

[0052] Among them, Y i Indicates the weight of the device type, C i It represents the type score of each building energy-using equipment of the same type; n is the number of building energy-using equipment of the same type.

[0053] The equipment weight can be evaluated according to the weight of the equipment type weight for different threshold ranges of actual power consumption, so as to calculate the final equipment weight according to the equipment type weight and actual power consumption of each building energy-consuming equipment.

[0054] Optionally, the calculation formula of device weight is expressed as:

[0055]

[0056] Among them, w i represents the equipment weight of the i-th building energy-consuming equipment, ρ is the equipment weight calculation coefficient, which is set to the corresponding constant according to the equipment type; P i represents the actual power consumption of the energy-consuming equipment in the i-th building; Y j is the type weight.

[0057] The spatial distribution function is obtained through the following steps: obtaining the equipment coverage area of ​​each of the building energy equipment through the equipment information of multiple building energy equipment; obtaining the distribution distance between different building energy equipment through the layout of multiple building energy equipment; defining a spatial distribution weight objective function for evaluating the spatial distribution weight of each building energy equipment according to the equipment coverage area of ​​each of the building energy equipment and the distribution distance between different building energy equipment; calculating the optimal spatial distribution weight using the spatial distribution weight objective function, and obtaining the spatial distribution function of the virtual scene training model according to the optimal spatial distribution weight.

[0058] The equipment coverage area is the area occupied by the building energy equipment on a two-dimensional horizontal plane, which can be obtained based on the maximum area of ​​the building energy equipment in the circumference; the occupied space is the volume occupied by the building energy equipment in three-dimensional space.

[0059] Define the distribution function: The distribution function should reflect the reasonable distribution of devices in the building space. For example, the distribution function can be defined based on the distance and coverage between devices:

[0060]

[0061] Among them, D represents the rationality of distribution, d ij represents the distance between the i-th device and the j-th device. The goal of the distribution function is to minimize D.

[0062] Distribution score: Calculate the distribution score of the device based on the distribution function and incorporate it into the comprehensive reward function. The formula for the distribution score is:

[0063]

[0064] Among them, S dist represents the distribution score, k dist is the distribution rationality reward coefficient.

[0065] The equipment maintenance function is obtained through the following steps: obtaining the installation position of each of the building energy equipment through the layout of multiple building energy equipment; obtaining the occupied space of each of the building energy equipment through the equipment information of multiple building energy equipment; defining an equipment maintenance difficulty objective function for evaluating the difficulty of equipment maintenance based on the installation position and occupied space between each of the building energy equipment; obtaining the optimal equipment maintenance difficulty using the equipment maintenance difficulty objective function, and obtaining the equipment maintenance function of the virtual scene training model based on the optimal equipment maintenance difficulty.

[0066] The equipment maintenance difficulty objective function can be defined based on the equipment installation location and occupied space to reflect the maintenance difficulty of the equipment:

[0067] Among them, M represents the convenience of maintenance, m i It represents the maintenance space of the i-th building energy-using equipment in the virtual building scene. The optimal maintenance difficulty is obtained by minimizing the equipment maintenance difficulty objective function M.

[0068] The space utilization function is obtained through the following steps: obtaining the installation position of each of the building energy equipment through the layout of multiple building energy equipment; obtaining the occupied space of each of the building energy equipment through the equipment information of multiple building energy equipment; defining an equipment space utilization objective function for evaluating the space utilization of each of the building energy equipment according to the ratio of the occupied space of each of the building energy equipment and the space of the corresponding virtual building scene; obtaining the optimal space utilization using the equipment space utilization objective function, and obtaining the space utilization function of the virtual scene training model according to the optimal space utilization.

[0069] Define the space utilization function: The space utilization function should reflect the ratio of the space occupied by the equipment to the building space. For example, the space utilization function can be defined based on the volume of the equipment and the volume of the building space:

[0070]

[0071] Among them, U represents space utilization, V i represents the volume of the ith device, V total Represents the total volume of the building space. The goal of the space utilization function is to minimize U.

[0072] Space utilization score: Calculate the space utilization score of the equipment based on the space utilization function and include it in the comprehensive reward function. The formula for the space utilization score is:

[0073]

[0074] Among them, S space represents the space utilization score, k space This is the space utilization bonus factor, and the preset values ​​are different for different equipment types.

[0075] The spatial illumination function is obtained through the following steps: the building energy equipment includes one or more lighting devices; according to the rated luminous flux and the lighting area of ​​each lighting device, the spatial illumination function of each lighting device is obtained corresponding to the preset standard illumination of the virtual building scene.

[0076] Define the spatial illumination function: The spatial illumination function should reflect the rationality of the lighting equipment in the building space. The light intensity should not be too large or too small and should be within a reasonable range.

[0077]

[0078] Where: S lx represents the spatial illumination score of the lighting equipment, k lx Indicates the space illumination bonus coefficient, which can be preset according to the model of the corresponding lighting equipment. Indicates the rated luminous flux of the lamp, S indicates the area, E indicates the std Indicates the standard illumination corresponding to different space styles in the following illumination standard table.

[0079] The illumination standard table is shown in Table 1 below:

[0080] Space Style Standard illumination bedroom 75lx bathroom 100lx kitchen 100lx living room 100lx Dining room 150lx

[0081] Table 1

[0082] The building scene information of each of the virtual building scenes includes: building space information and building scene type; the equipment information of multiple building energy-using equipment includes: any one or more of size, shape, quantity, installation method, accessory specifications and operating parameters.

[0083] When optimizing data through a comprehensive reward function, for example, if the cooling capacity of a certain model of air conditioner is 4500W and the power consumption is 1500W, its energy efficiency is:

[0084]

[0085] Assume that there are three air conditioning systems in the current building, with energy efficiencies of 3, 2.5, and 2.8, and rated powers of 1500w, 1000w, and 1000w. The type scores are 29 points, 32 points, and 36 points, respectively. The equipment type weight Y is obtained by comprehensive calculation. 1 , Y 2 , Y 3 :

[0086]

[0087] The equipment weight calculation coefficient ρ of this equipment type is taken as 3.04, and the equipment weight w is calculated by comprehensively considering the equipment power and type weight. 1 , w 2 , w 3 :

[0088]

[0089] The energy efficiency optimization reward score can be calculated based on the optimal actual energy efficiency and equipment weight of each building energy-using equipment, and then the optimization reward score can be incorporated into the reward function of the virtual scene training model.

[0090] The optimization reward score can be expressed as:

[0091]

[0092] Among them, S eff represents the energy efficiency optimization reward score, w i represents the device weight of the i-th device, η i represents the optimal actual energy efficiency of the i-th building energy-using equipment, k eff is the energy efficiency optimization bonus coefficient, which is a constant obtained according to the corresponding equipment type, and n is the number of energy-using equipment in the building.

[0093] If the energy efficiency optimization reward coefficient is 1.0, the energy efficiency optimization reward score is:

[0094] S eff =1.0*(0.39·3+0.287·2.5+0.322·2.8)=2.79;

[0095] The spatial distribution weight objective function reflects the reasonable distribution of equipment in the building space and is defined based on the distance and coverage between devices:

[0096]

[0097] Among them, D represents the rationality of distribution, d ij represents the distribution distance between the i-th building energy equipment and the j-th building energy equipment, and n is the number of building energy equipment. The optimal spatial distribution weight is obtained by minimizing the spatial distribution weight objective function D.

[0098] Optionally, the distribution score of the device is calculated based on the optimal spatial distribution weight and incorporated into the reward function of the virtual scene training model. The formula for the distribution score is:

[0099]

[0100] Among them, S dist represents the distribution score; k dist is the distribution rationality reward coefficient, and is a constant obtained according to the building scene type of the virtual building scene.

[0101] For example, if the distances between the three air conditioning systems are 5m, 6m, and 7m respectively, the spatial distribution weight objective function is:

[0102]

[0103] Taking the distribution rationality reward coefficient as 1.0, calculate the distribution score:

[0104]

[0105] Optionally, the maintenance score of the equipment is calculated based on the equipment maintenance difficulty objective function and incorporated into the reward function of the virtual scene training model. The maintenance score formula is:

[0106] Among them, S main represents the maintenance score; k main is the maintenance convenience bonus coefficient, which is a constant obtained according to the equipment type of the building's energy-consuming equipment; M is the equipment maintenance difficulty objective function.

[0107] For example: The space occupied by maintaining three air conditioning systems is 2m 2 , 2.5m 2 and 3m 2 , then the equipment maintenance difficulty objective function is:

[0108]

[0109] Taking the maintenance convenience bonus coefficient as 1.0, calculate the maintenance score:

[0110]

[0111] Calculate the ratio of the volume of each air conditioning system to the volume of the building space: For example, the volume of the three air conditioning systems is 0.12m 3 、0.15m 3 and 0.18m 3 , the total volume of the building space is 100m 3 , then the space utilization function is:

[0112]

[0113] Taking the space utilization bonus coefficient as 0.01, calculate the space utilization score:

[0114]

[0115] In the learning process of the virtual scene training model, the layout is adjusted and optimized through multiple iterations until the optimal solution is found. Optionally, the weight coefficients of the energy efficiency optimization reward score, distribution score, maintenance score, space utilization score and space illumination can be adjusted, and the comprehensive reward function of the virtual scene training model can be obtained by summing up the results of each score * the weight coefficient of each score, and the virtual scene training model can be optimized in many aspects by combining all the scoring results.

[0116] After the virtual scene training model outputs the layout of the multiple building energy-using equipment of the virtual scene data to be detected, the virtual building scene can be generated according to the final layout through the Revit software based on the building scene information of the virtual building scene. Through the API interface of Revit, the layout plan is converted into a visual building model, which is convenient for designers to make further modifications and adjustments.

[0117] Example 2

[0118] like Figure 2 As shown, the embodiment of the present application provides a building energy equipment intelligent layout system, including:

[0119] The training data acquisition module is used to collect multiple sets of virtual scene training data according to multiple virtual building scenes; each set of the virtual scene training data includes the building scene information of each virtual building scene, the equipment information of multiple building energy-using equipment in each virtual building scene, and the layout data of the building energy-using equipment;

[0120] A reward function definition module: used to define a comprehensive reward function based on the energy efficiency function, spatial distribution function, equipment maintenance function, space utilization function and spatial illumination function of the virtual building scene;

[0121] A scene model training module: used for selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model through multiple sets of virtual scene training data, and optimizing the trained initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model;

[0122] Equipment scheme layout module: used to obtain the layout scheme of the scene data to be tested through the virtual scene training model to layout the building energy equipment.

[0123] In summary, the embodiments of the present application provide a method and system for intelligent layout of building energy equipment:

[0124] According to multiple virtual building scenes, building scene information, multiple building energy equipment, the performance of multiple building energy equipment and the layout of multiple building energy equipment are collected respectively, and a virtual scene training model for the scene layout of building energy equipment is trained, so as to output the layout of multiple building energy equipment of the virtual scene data to be tested; and the virtual scene training model is optimized by using the comprehensive reward function defined by the energy efficiency function, spatial distribution function, equipment maintenance function and spatial illumination function of the virtual building scene; the layout scheme of the scene data to be tested is obtained by the optimized virtual scene training model, so that the model can quickly and accurately obtain the layout of building energy equipment that better meets the actual needs of the scene. The present invention solves the problem that it is difficult to achieve an ideal layout effect when facing a complex and changeable building environment, resulting in low design efficiency and difficulty in meeting actual needs.

[0125] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for intelligent layout of building energy equipment, characterized in that: include: Collect multiple sets of virtual scene training data according to multiple virtual building scenes; Each group of the virtual scene training data includes the building scene information of each virtual building scene, the equipment information of a plurality of the building energy equipment in each virtual building scene, and the layout data of the building energy equipment; Defining a comprehensive reward function based on the energy efficiency function, spatial distribution function, equipment maintenance function, space utilization function and spatial illumination function of the virtual building scene; Selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model using multiple sets of the virtual scene training data, and optimizing the trained initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model; The layout plan of the scene data to be tested is obtained through the virtual scene training model to layout the building energy equipment.

2. A method for intelligent layout of building energy equipment according to claim 1, characterized in that: The building energy equipment layout data includes the orientation, position and connection type between each building energy equipment and the corresponding virtual building scene; the connection type includes the number of connections, connector specifications, distributable space and fixing method.

3. A method for intelligent layout of building energy equipment according to claim 2, characterized in that: The energy efficiency function is obtained by the following steps: Obtaining actual production capacity and actual power consumption through equipment information of each of the energy-using equipment in the building; defining an actual energy efficiency objective function of each of the energy-using equipment in the building according to the ratio of the actual production capacity and actual power consumption of each of the energy-using equipment in the building; and obtaining the optimal actual energy efficiency by maximizing the actual energy efficiency objective function; Analyzing type weights by using building energy equipment layout data of a plurality of said building energy equipments; The equipment weight is calculated according to the type weight and the actual power consumption; and the energy efficiency function of the virtual scene training model is obtained according to the optimal actual energy efficiency and equipment weight of each of the energy-using equipment in the building.

4. A method for intelligent layout of building energy equipment according to claim 3, characterized in that: The analyzing type weights through the building energy equipment layout data of the plurality of building energy equipments comprises: The equipment type of each of the building energy equipment is obtained through the equipment information of multiple building energy equipment; one or more of the orientation, position and connection type are scored according to the preset scoring rules of the equipment type of each of the building energy equipment, and the type weight of the building energy equipment is obtained according to the scoring results.

5. The intelligent layout method of building energy equipment according to claim 1, characterized in that: The spatial distribution function is obtained through the following steps: obtaining the equipment coverage area of ​​each of the building energy equipment through the equipment information of multiple building energy equipment; obtaining the distribution distance between different building energy equipment through the layout of multiple building energy equipment; defining a spatial distribution weight objective function for evaluating the spatial distribution weight of each building energy equipment according to the equipment coverage area of ​​each of the building energy equipment and the distribution distance between different building energy equipment; calculating the optimal spatial distribution weight using the spatial distribution weight objective function, and obtaining the spatial distribution function of the virtual scene training model according to the optimal spatial distribution weight.

6. The intelligent layout method of building energy equipment according to claim 1, characterized in that: The equipment maintenance function is obtained through the following steps: obtaining the installation position of each of the building energy equipment through the layout of multiple building energy equipment; obtaining the occupied space of each of the building energy equipment through the equipment information of multiple building energy equipment; defining an equipment maintenance difficulty objective function for evaluating the difficulty of equipment maintenance based on the installation position and occupied space between each of the building energy equipment; obtaining the optimal equipment maintenance difficulty using the equipment maintenance difficulty objective function, and obtaining the equipment maintenance function of the virtual scene training model based on the optimal equipment maintenance difficulty.

7. The intelligent layout method of building energy equipment according to claim 1, characterized in that: The space utilization function is obtained through the following steps: obtaining the installation position of each of the building energy equipment through the layout of multiple building energy equipment; obtaining the occupied space of each of the building energy equipment through the equipment information of multiple building energy equipment; defining an equipment space utilization objective function for evaluating the space utilization of each of the building energy equipment according to the ratio of the occupied space of each of the building energy equipment and the space of the corresponding virtual building scene; obtaining the optimal space utilization using the equipment space utilization objective function, and obtaining the space utilization function of the virtual scene training model according to the optimal space utilization.

8. The intelligent layout method of building energy equipment according to claim 1, characterized in that: The spatial illumination function is obtained through the following steps: the building energy equipment includes one or more lighting devices; according to the rated luminous flux and the lighting area of ​​each lighting device, the spatial illumination function of each lighting device is obtained corresponding to the preset standard illumination of the virtual building scene.

9. The intelligent layout method of building energy equipment according to claim 1, characterized in that: The building scene information of each of the virtual building scenes includes: building space information and building scene type; the equipment information of multiple building energy-using equipment includes: any one or more of size, shape, quantity, installation method, accessory specifications and operating parameters.

10. An intelligent layout system for building energy equipment, characterized in that: include: Training data collection module: used to collect multiple sets of virtual scene training data according to multiple virtual building scenes; Each group of the virtual scene training data includes the building scene information of each virtual building scene, the equipment information of a plurality of the building energy equipment in each virtual building scene, and the layout data of the building energy equipment; A reward function definition module: used to define a comprehensive reward function based on the energy efficiency function, spatial distribution function, equipment maintenance function, space utilization function and spatial illumination function of the virtual building scene; A scene model training module: used for selecting a pre-trained initial virtual scene training model; training the initial virtual scene training model through multiple sets of virtual scene training data, and optimizing the trained initial virtual scene training model based on the comprehensive reward function to obtain a virtual scene training model; Equipment scheme layout module: used to obtain the layout scheme of the scene data to be tested through the virtual scene training model to layout the building energy equipment.

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