A multi-objective optimization design method for building wrapping cavity

Abstract

The present invention discloses a multi-objective optimization design method for a building wrapping cavity layer, which takes the form factor of the building wrapping cavity layer as the optimization design factor, takes the percentage of effective indoor lighting illumination, energy usage intensity and indoor thermal discomfort time percentage as the optimization target, and uses the improved intensity Pareto evolutionary algorithm and the hypervolume estimation algorithm to generate the Pareto optimal solution set, providing a basis for cavity layer design decisions based on environmental performance. The present invention performs an overall single optimization design of building wrapping cavity layers in different orientations, has high design efficiency and scientificity, and can obtain the optimal solution of the building wrapping cavity layer.

Description

Technical Field

[0001] The present invention belongs to the technical field of green buildings, and particularly relates to a multi-objective optimization design method for a building wrapped cavity layer. Background Art

[0002] A building wrapped cavity layer is a cavity layer that controls the heat transfer between the inside and outside of a building through a multi-layer enclosure structure and a continuous thermal buffer space between the two in an overall wrapped spatial layout. Its characteristics are that the cavity layer space is continuously connected, the internal functional space is integrally wrapped, and it has different cavity layer depths according to different regulation functions in each orientation, which can improve the comfort of the internal space of the building and the energy use efficiency.

[0003] Current building design methods often make individual designs for the wrapped cavity layers in different orientations. The existing technology often takes performance goals as the guide, integrates parametric modeling, performance simulation tools and optimization algorithms, and conducts an optimization search for the design factors of the wrapped cavity layer, improving the efficiency and scientificity of the design.

[0004] However, when comprehensively considering the wrapped cavity layers in different orientations, if individual designs are still made, the working efficiency is low and it is difficult to obtain an overall optimal solution. The reason is the lack of a parametric modeling method and an optimization design method for describing the form characteristics of the building wrapped cavity layer. Summary of the Invention

[0005] The technical problem to be solved by the present invention is how to overcome the above defects of the existing technology, provide a multi-objective optimization design method for a building wrapped cavity layer, use the form factor of the building wrapped cavity layer as the optimization design factor, take the percentage of effective indoor daylight illumination, energy use intensity, and the percentage of indoor thermal discomfort time as the optimization objectives, and use the improved strength Pareto evolutionary algorithm (SPEA-2) and hypervolume estimation algorithm (HypE) to generate a Pareto optimal solution set, providing a basis for the cavity layer design decision based on environmental performance.

[0006] The present invention is realized through the following technical solutions:

[0007] A multi-objective optimization design method for a building wrapped cavity layer, comprising the following steps:

[0008] Step 1: Parametric modeling of the form factor of the building wrapped cavity layer; the building wrapped cavity layer is a cavity layer space that wraps the building use space in the four directions of east, south, west, and north. Among them, windows are provided on the outer interface of the south cavity layer, the inner interface of the south cavity layer, the outer interface of the north cavity layer, and the inner interface of the north cavity layer. Specifically, it includes the following sub-steps:

[0009] 1.1: Define the design factors for describing the form characteristics of the building wrapped cavity layer;

[0010] 1.2: Construct a parametric model of the building envelope cavity layer according to the design factors;

[0011] In step 1.1, the design factors describing the formal characteristics of the building envelope cavity layer include: control point P on the south - west side of the cavity layer plane 1 The distance moved by the south - west end point of the building plane in the negative x - axis direction, control point P on the south - west side of the cavity layer plane 1 The distance moved by the south - west end point of the building plane in the negative y - axis direction, control point P on the south - east side of the cavity layer plane 2 The distance moved by the south - east end point of the building plane in the positive x - axis direction, control point P on the south - east side of the cavity layer plane 2 The distance moved by the south - east end point of the building plane in the negative y - axis direction, control point P on the north - east side of the cavity layer plane 3 The distance moved by the north - east end point of the building plane in the positive x - axis direction, control point P on the north - east side of the cavity layer plane 3 The distance moved by the north - east end point of the building plane in the positive y - axis direction, control point P on the north - west side of the cavity layer plane 4 The distance moved by the north - west end point of the building plane in the negative x - axis direction, control point P on the north - west side of the cavity layer plane 4 The distance moved by the north - west end point of the building plane in the positive y - axis direction, the window - wall ratio of the south - facing cavity layer outer interface, the window - wall ratio of the south - facing cavity layer inner interface, the window - wall ratio of the north - facing cavity layer outer interface, and the window - wall ratio of the north - facing cavity layer inner interface. Based on the defined design factors of the building envelope cavity layer, establish a parametric physical model of the building envelope cavity layer in the parametric design platform;

[0012] Step 2: Establish a multi - objective optimization design model of the building envelope cavity layer;

[0013] Step 3: Make a design decision by integrating the Pareto optimal solution set and the sorting result.

[0014] Step 2 includes the following sub - steps:

[0015] 2.1: Establish a building performance model of the building envelope cavity layer according to the optimization objectives;

[0016] 2.2: Establish a multi - objective optimization design model based on the analysis results of building performance simulation.

[0017] In step 2.1, it is necessary to define the optimization objectives first. The first optimization objective is the percentage of indoor effective daylighting illuminance in the building's usable space, the second optimization objective is the indoor energy use intensity in the building's usable space, and the third optimization objective is the percentage of indoor annual thermal discomfort time in the building's usable space.

[0018] In step 1, the parametric design platform is the Rhino - Grasshopper platform.

[0019] In Step 2.1, within the Rhino-Grasshopper platform, use the Ladybug tools plug-in to call the Radiance simulation engine to calculate the percentage of effective indoor daylight illumination in the building's usable space, and call the EnergyPlus simulation engine to calculate the indoor energy use intensity in the building's usable space and the percentage of annual indoor thermal discomfort time in the building's usable space;

[0020] In Step 2.2, within the Rhino-Grasshopper platform, use the Octopus plug-in to establish a multi-objective optimization design model based on the improved strength Pareto evolutionary algorithm and the hypervolume estimation algorithm. All design variables are imported as genes into the input end of Octopus, and the three optimization objectives are at the output end.

[0021] Sort all the solutions according to the following fitness function, extract the optimal solution from them, and comprehensively compare the optimal solutions of the three single performances to make a final design decision.

[0022] y = (UDI i - UDI min )C 1 - (EUI i - EUI min )C 2 - (TDP i - TDP min )C 3

[0023]

[0024] Among them, the y value is the comprehensive evaluation value of the three performance indicators. The optimization process can automatically find the optimal solution. By adjusting the design factors, the maximum performance evaluation value can be obtained;

[0025] UDI refers to the percentage of effective daylight illumination;

[0026] UDI max and UDI min refer to the maximum and minimum values of the percentage of effective daylight illumination among all solutions;

[0027] EUI refers to the energy use intensity;

[0028] EUI max and EUI min refer to the maximum and minimum values of the energy use intensity among all solutions;

[0029] TDP refers to the percentage of thermal discomfort time;

[0030] TDP max and TDP minIt refers to the maximum and minimum percentages of the time of thermal discomfort among all solutions.

[0031] The advantages of the present invention are as follows:

[0032] First, design factors for describing the formal characteristics of the building-wrapped cavity layer are proposed. The parametric physical model established thereby helps designers conveniently obtain cavity layer design schemes of different forms. The parametric physical model can be conveniently connected to the building performance simulation platform, and by adjusting the design factors, the corresponding optimized target values can be calculated.

[0033] Second, the present invention proposes a multi-objective optimization design method for the building-wrapped cavity layer guided by the percentage of indoor effective daylight illumination, energy use intensity, and annual percentage of thermal discomfort time in the building's usable space, which is used to support the design of the building-wrapped cavity layer driven by environmental performance and helps to promote low-carbon energy conservation in the building field.

[0034] Third, in the application of the present invention, the number of control points in step 1.1 can be adjusted according to the actual form of the building-wrapped cavity layer, which has wide applicability and helps architects make scientific and effective design decisions during the design process.

[0035] Fourth, the present invention conducts an overall single optimization design for the building-wrapped cavity layer in different orientations, which has high design efficiency and scientificity and can obtain the optimal solution of the building-wrapped cavity layer. Description of the Drawings

[0036] Figure 1 is the framework diagram of the multi-objective optimization design method for the building-wrapped cavity layer in the present invention;

[0037] Figure 2 is the schematic diagram of the design factors of the building-wrapped cavity layer in the present invention;

[0038] Figure 3 is the construction diagram of the physical model, performance simulation model, and optimization model of the building-wrapped cavity layer in the present invention;

[0039] Figure 4 is the schematic diagram of all solutions of the optimized building-wrapped cavity layer in the present invention;

[0040] Figure 5 is the schematic diagram of the Pareto solution and the optimal solution of the building-wrapped cavity layer in the present invention;

[0041] Among them, 1 - Control point P on the southwest side of the cavity layer plane 1 is the distance moved by the southwest end point of the building plane in the negative x-axis direction, 2 - Control point P on the southwest side of the cavity layer plane 1 is the distance moved by the southwest end point of the building plane in the negative y-axis direction, 3 - Control point P on the southeast side of the cavity layer plane 2The distance that the southeast end point of the building plan moves in the positive x-axis direction, the control point P on the southeast side of the 4-chamber layer plane 2 The distance that the southeast end point of the building plan moves in the negative y-axis direction, the control point P on the northeast side of the 5-chamber layer plane 3 The distance that the northeast end point of the building plan moves in the positive x-axis direction, the control point P on the northeast side of the 6-chamber layer plane 3 The distance that the northeast end point of the building plan moves in the positive y-axis direction, the control point P on the northwest side of the 7-chamber layer plane 4 The distance that the northwest end point of the building plan moves in the negative x-axis direction, the control point P on the northwest side of the 8-chamber layer plane 4 The distance that the northwest end point of the building plan moves in the positive y-axis direction, the window-wall ratio (WWRse) of the outer interface of the 9-south-facing chamber layer, the window-wall ratio (WWRsi) of the inner interface of the 10-south-facing chamber layer, the window-wall ratio (WWRne) of the outer interface of the 11-north-facing chamber layer, the window-wall ratio (WWRni) of the inner interface of the 12-north-facing chamber layer Detailed implementation manners

[0042] The following takes a certain office building unit and a four-direction wrapped chamber space as an example in combination with the accompanying drawings of the specification for detailed description:

[0043] As shown in the attached Figure 1 , a multi-objective optimization design method for a building wrapped chamber provided by an embodiment of the present invention includes the following steps:

[0044] Step 1: Parametric modeling of the form factor of the building wrapped chamber;

[0045] 1.1: Define the design factors describing the form characteristics of the building wrapped chamber;

[0046] 1.2: Construct a parametric model of the building wrapped chamber according to the design factors.

[0047] Step 2: Establish a multi-objective optimization design model for the building wrapped chamber;

[0048] 2.1: Establish a building performance model of the building wrapped chamber according to the optimization objectives;

[0049] 2.2: Establish a multi-objective optimization design model based on the analysis results of building performance simulation.

[0050] Step 3: Make a design decision by integrating the Pareto optimal solution set and the sorting result.

[0051] The building wrapped chamber is as shown in Figure 2As shown, it is a cavity space that wraps the office space in the four directions of east, south, west, and north. Windows are provided on the outer interface of the south-facing cavity layer, the inner interface of the south-facing cavity layer, the outer interface of the north-facing cavity layer, and the inner interface of the north-facing cavity layer. The design factors describing the form characteristics of the building-wrapped cavity layer in step 1.1 include: control point P on the southwest side of the cavity layer plane 1 The distance moved by the southwest end point of the building plane in the negative x-axis direction, control point P on the southwest side of the cavity layer plane 1 The distance moved by the southwest end point of the building plane in the negative y-axis direction, control point P on the southeast side of the cavity layer plane 2 The distance moved by the southeast end point of the building plane in the positive x-axis direction, control point P on the southeast side of the cavity layer plane 2 The distance moved by the southeast end point of the building plane in the negative y-axis direction, control point P on the northeast side of the cavity layer plane 3 The distance moved by the northeast end point of the building plane in the positive x-axis direction, control point P on the northeast side of the cavity layer plane 3 The distance moved by the northeast end point of the building plane in the positive y-axis direction, control point P on the northwest side of the cavity layer plane 4 The distance moved by the northwest end point of the building plane in the negative x-axis direction, control point P on the northwest side of the cavity layer plane 4 The distance moved by the northwest end point of the building plane in the positive y-axis direction, the window-wall ratio (WWRse) of the outer interface of the south-facing cavity layer, the window-wall ratio (WWRsi) of the inner interface of the south-facing cavity layer, the window-wall ratio (WWRne) of the outer interface of the north-facing cavity layer, and the window-wall ratio (WWRni) of the inner interface of the north-facing cavity layer. Based on the defined design factors of the building-wrapped cavity layer, a parametric physical model of the building-wrapped cavity layer is established within the Rhino-Grasshopper platform.

[0052] In step 2.1, it is necessary to define the optimization objectives first. The indoor effective daylighting illuminance percentage (UDI) of the building's usable space is taken as the first optimization objective, the indoor energy use intensity (EUI) of the building's usable space is taken as the second optimization objective, and the indoor annual thermal discomfort time percentage (TDP) of the building's usable space is taken as the third optimization objective.

[0053] Within the Rhino-Grasshopper platform, use the Ladybug tools plugin to call the Radiance simulation engine to calculate the indoor effective daylighting illuminance percentage of the building's usable space, and call the EnergyPlus simulation engine to calculate the indoor energy use intensity and the indoor annual thermal discomfort time percentage of the building's usable space.

[0054] In Step 2.2, within the Rhino-Grasshopper platform, using the Octopus plug-in, a multi-objective optimization design model is established based on the improved Strength Pareto Evolutionary Algorithm (SPEA-2) and the Hypervolume Estimation Algorithm (HypE). All design variables are imported as genes into the input end of Octopus, and the three optimization objectives are at the output end.

[0055] In Step 3, all solutions are sorted according to the following fitness function, the optimal solution is extracted from them, and at the same time, the optimal solutions of the three single performances are comprehensively compared to make the final design decision.

[0056] y = (UDI i - UDI min )C 1 -(EUI i - EUI min )C 2 -(TDP i - TDP min )C 3

[0057]

[0058] Among them, the y value is the comprehensive evaluation value of the three performance indicators. The optimization process can automatically search for the optimum. By adjusting the design factors, the maximum performance evaluation value can be obtained. UDI (Useful Daylight Illuminance) refers to the percentage of useful daylight illuminance. UDI max and UDI min refer to the maximum and minimum values of the percentage of useful daylight illuminance among all solutions; EUI (Energy Use Intensity) refers to the energy use intensity. EUI max and EUI min refer to the maximum and minimum values of the energy use intensity among all solutions; TDP (Thermal Discomfort Percentage) refers to the percentage of thermal discomfort time. TDP max and TDP min refer to the maximum and minimum values of the percentage of thermal discomfort time among all solutions.

[0059] The construction diagrams of the above various models are as shown in Figure 3 shown.

[0060] The results of all solutions after optimization are as shown in Figure 4 shown, and the results of the Pareto solution and the optimal solution after optimization are as shown in Figure 5 shown.

[0061] In this embodiment, three performance objectives are weighed and considered, and it is analyzed that the 219th solution is the optimal solution. The values of its design factors are 1.7, 1.7, 1.9, 1, 1.1, 1.9, 1.8, 1.8, 0.241, 0.816, 0.389, and 0.579 respectively; the values of its three performance objectives UDI, EUI, and TDP are 70.9%, 66.6 kWh / m2 / y, and 70.2% respectively.

Claims

1. A multi-objective optimization design method for a building wrapping cavity layer, characterized in that: The following steps are involved: Step 1: parametric modeling of the form factor of the building wrapping cavity layer; the building wrapping cavity layer is a cavity layer space that wraps the building use space in the four directions of east, south, west and north, wherein the outer interface of the south cavity layer, the inner interface of the south cavity layer, the outer interface of the north cavity layer and the inner interface of the north cavity layer are provided with windows, specifically including the following sub-steps: 1.1: Define the design factors that characterize the building wrap cavity form; 1.2: Construct a parametric model of the building wrap cavity based on the design factors; In step 1.1, the design factors describing the characteristics of the building wrapping cavity layer form include: the distance of the southwest control point P1 of the cavity layer plane moved from the southwest end point of the building plane in the negative direction of the x-axis, the distance of the southwest control point P1 of the cavity layer plane moved from the southwest end point of the building plane in the negative direction of the y-axis, the distance of the southeast control point P2 of the cavity layer plane moved from the southeast end point of the building plane in the positive direction of the x-axis, the distance of the southeast control point P2 of the cavity layer plane moved from the southeast end point of the building plane in the negative direction of the y-axis, and the distance of the northeast control point P3 of the cavity layer plane moved from the northeast end point of the building plane in the positive direction of the x-axis. Based on the defined building wrapping cavity design factors, a parametric physical model of the building wrapping cavity is established in the parametric design platform based on the distance of movement of the control point P3 on the northeast side of the cavity plane from the northeast end point of the building plane in the positive direction of the y-axis, the distance of movement of the control point P4 on the northwest side of the cavity plane from the northwest end point of the building plane in the negative direction of the x-axis, the distance of movement of the control point P4 on the northwest side of the cavity plane from the northwest end point of the building plane in the positive direction of the y-axis, the window-to-wall ratio of the outer interface of the south cavity layer, the window-to-wall ratio of the inner interface of the south cavity layer, the window-to-wall ratio of the outer interface of the north cavity layer and the window-to-wall ratio of the inner interface of the north cavity layer; Step 2: Establish a multi-objective optimization design model for the building wrapping cavity layer; Step 3: Make design decisions based on the Pareto optimal solution set and ranking results; In step 1, the parametric design platform is a Rhino-Grasshopper platform; In step 2.1, the Ladybug tools plug-in is used in the Rhino-Grasshopper platform to call the Radiance simulation engine to calculate the percentage of indoor effective lighting illumination of the building's use space, and the EnergyPlus simulation engine is called to calculate the indoor energy intensity of the building's use space and the percentage of indoor thermal discomfort time of the building's use space throughout the year; In step 2.2, the Octopus plug-in was used in the Rhino-Grasshopper platform to establish a multi-objective optimization design model based on the improved intensity Pareto evolutionary algorithm and the hypervolume estimation algorithm. All design variables were imported into the input of Octopus as genes, and the three optimization objectives were used as outputs. All solutions are sorted according to the following fitness function, the optimal solution is extracted from them, and the optimal solutions of the three individual performances are comprehensively compared to make the final design decision. y=(UDI i -UDI min )C1-(EUI i -EUI min )C2-(TDP i -TDP min )C3 Among them, the y value is the comprehensive evaluation value of the three performance indicators. The optimization process can automatically find the best value and obtain the maximum performance evaluation value by adjusting the design factors; UDI refers to the percentage of effective daylighting illumination; UDI max and UDI min It refers to the maximum and minimum values ​​of the effective lighting illuminance percentage among all solutions; EUI refers to energy use intensity; EUI max and EUI min It refers to the maximum and minimum values ​​of energy intensity among all solutions; TDP refers to the percentage of thermal discomfort time; TDP max and TDP min It refers to the maximum and minimum values ​​of the percentage of thermal discomfort time among all solutions.

2. The multi-objective optimization design method of the building wrapping cavity layer according to claim 1 is characterized in that: Step 2 includes the following sub-steps: 2.1: Establish the building performance model of the building wrap cavity layer according to the optimization objectives; 2.2: Establish a multi-objective optimization design model based on the analysis results of building performance simulation.

3. The multi-objective optimization design method of the building wrapping cavity layer according to claim 2 is characterized in that: In step 2.1, the optimization objectives must be defined first, with the percentage of indoor effective lighting illumination in the building's use space as optimization objective one, the indoor energy intensity in the building's use space as optimization objective two, and the percentage of indoor thermal discomfort time in the building's use space throughout the year as optimization objective three.

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