A method for simulating and evaluating optimization of photovoltaic performance of a variable building skin

Abstract

The application relates to a photovoltaic performance simulation evaluation optimization method of a variable building skin, relates to the technical field of building engineering, and deeply digitally couples physical deformation characteristics of the variable skin with urban high-density environment light radiation conditions, establishes a multi-dimensional comprehensive performance evaluation index system, determines the best time-sharing morphological change logic of a target building under specific light climate environment by using a multi-objective optimization algorithm, and determines a control strategy of an active curtain wall control system. The strategy fully considers specific influences of continuous complex morphological changes of the active curtain wall on actual performance of photovoltaic panels distributed on the surface, and therefore avoids problems of solar energy resource waste and air conditioning energy consumption soaring caused by improper deformation caused by existing control methods.

Description

Technical Field

[0001] This application relates to the field of building engineering technology, specifically a method for simulation evaluation and optimization of photovoltaic performance of variable building skins. Background Technology

[0002] With the increasing global industrialization and the overexploitation of non-renewable energy sources, large amounts of greenhouse gases have been released, leading to rising global temperatures and triggering a series of environmental degradation problems. Statistics show that my country's construction speed has increased year by year, and the urban and rural building area has increased significantly. From 2005 to 2020, my country's total carbon emissions from the entire building process rose from 2.23 billion tons of CO2 to 5.08 billion tons of CO2, 2.3 times the original amount, with an average annual growth rate of 5.6%. As an industry with extremely high energy consumption and carbon emissions, the application of new energy sources in the construction industry is becoming increasingly important. Of the energy consumed by buildings, 80% comes from fossil fuels. To address future environmental problems, the application of renewable energy in buildings has received increasing support from governments worldwide. Among these, building-integrated photovoltaic (BIPV) power generation currently accounts for the largest share of renewable energy power generation and has the widest application range.

[0003] With urban development, the number of high-rise buildings in cities is increasing, and large building curtain wall systems have significant photovoltaic potential. Current building-integrated photovoltaic (BIPV) technology allows photovoltaic systems to be integrated onto various building surfaces, including exterior walls, windows, and curtain wall systems. Facade photovoltaic systems utilize the building's vertical walls to install solar panels, enabling the deployment of larger solar panel areas and thus generating more energy, thereby improving the building's energy performance.

[0004] An active curtain wall is a building curtain wall system with a variable structural form. It can change its shape by folding, changing, or rotating according to the external environment, thereby changing the shading angle, creating an excellent building light and heat environment, and regulating indoor comfort.

[0005] Existing active curtain wall control systems often operate based on simple indoor temperature or light control logic, without considering the specific impact of continuous and complex morphological changes generated by the active curtain wall on the actual efficiency of the photovoltaic panels distributed on its surface. Therefore, existing control methods result in the waste of solar energy resources and a surge in air conditioning energy consumption due to improper deformation. Summary of the Invention

[0006] The purpose of this invention is to address the issue that existing active curtain wall control systems often operate based on simple indoor temperature or light control logic, without considering the specific impact of continuous and complex morphological changes generated by the active curtain wall on the actual efficiency of the photovoltaic panels distributed on its surface. Therefore, existing control methods result in the waste of solar energy resources and the problem of soaring air conditioning energy consumption due to improper deformation. This invention provides a photovoltaic efficiency simulation evaluation and optimization method for variable building skins.

[0007] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0008] A method for simulating, evaluating, and optimizing the photovoltaic efficiency of a variable building skin includes the following steps:

[0009] Step 1: Establish a model of the urban environment and urban shading, and a parametric model of the variable building skin system;

[0010] Step 2: Define the evaluation criteria for assessing variable building skins;

[0011] Step 3: Determine the engineering constraint boundary conditions based on the urban environment and urban shading model, and use the parametric model of the variable building skin system to evolve and simulate the changes in building surface morphology sample data within the engineering constraint boundary conditions. Then, combine the evaluation index as the core objective function to iterate the three-dimensional morphological parameters of each building curtain wall unit to obtain the optimal time-sharing morphological change logic of the variable building skin, and use this logic as the variable skin control strategy.

[0012] Furthermore, the specific steps of step 1 are as follows:

[0013] Step 11: Obtain natural condition information, collect and parameterize land parcel features, and then use the natural condition information and land parcel features to establish an urban environment and urban shading model;

[0014] Step 12: Use the Rhino 3D modeling platform to construct a parametric model of the variable building skin system that includes the morphological changes of standard layers and the logic of continuous physical deformation between layers.

[0015] Furthermore, the natural condition information includes the climate zones of the target region, hourly temperatures throughout the year, dry / wet bulb temperatures, precipitation probability, solar radiation intensity, and solar trajectory in different seasons.

[0016] Furthermore, the characteristics of the plot include the ratio of building height to street width, the depth and width of surrounding buildings, the distance between buildings, and the plot ratio.

[0017] Furthermore, the evaluation metrics used in step 2 to assess the variable building skin include photovoltaic energy efficiency, photovoltaic economic efficiency, and the shape-to-photovoltaic loss ratio.

[0018] Furthermore, the photovoltaic energy efficiency is expressed as:

[0019] ,

[0020] in, Photovoltaic energy efficiency for buildings with variable shapes The total annual solar radiation for the area selected for buildings with varying shapes. The total annual solar radiation for the selected area of ​​standard-shaped buildings.

[0021] Furthermore, the photovoltaic economic efficiency is expressed as:

[0022] ,

[0023] in, To improve the economic efficiency of photovoltaics in buildings with variable shapes. The total annual solar radiation for the area selected for buildings with varying shapes. The total annual solar radiation for the area selected for standard-shaped buildings. Selecting the area for buildings with varying shapes. Select the area for standard-shaped buildings.

[0024] Furthermore, the shape-photovoltaic loss ratio is expressed as:

[0025] ,

[0026] in, For the shape-photovoltaic loss ratio of buildings with variable forms, The total annual solar radiation for the area selected for buildings with varying shapes. The total annual solar radiation for the area selected for standard-shaped buildings. To change the shape and volume of the building, For standard-shaped building volume, To vary the surface area of ​​the building's shape. The surface area of ​​a standard-shaped building.

[0027] Furthermore, the specific steps of step 3 are as follows:

[0028] Step 31: Maximize the photovoltaic energy efficiency and photovoltaic economic efficiency as fitness objective functions, and minimize the size-photovoltaic depreciation ratio as fitness objective functions.

[0029] Step 32: Determine the engineering constraint boundary conditions based on the urban environment and urban shading model, and use the parametric model of the variable building skin system to evolve within the engineering constraint boundary conditions and simulate and generate sample data of building surface morphology changes;

[0030] Step 33: Based on the morphological change sample data, extract the distribution characteristics of the parameters, and based on the fitness objective function in Step 31, iterate the three-dimensional morphological parameters of each building curtain wall unit to obtain the optimal time-sharing morphological change logic of the variable building skin, and use this logic as the variable skin control strategy.

[0031] Furthermore, the morphology optimization in step 33 is performed using the Octopus plugin environment on the Grasshopper platform.

[0032] The beneficial effects of this invention are:

[0033] This application deeply digitally couples the physical deformation characteristics of the variable skin with the high-density ambient light radiation conditions of the city. By establishing a multi-dimensional comprehensive performance evaluation index system, a multi-objective optimization algorithm is used to determine the optimal time-sharing morphological change logic of the target building under specific light and climate conditions, thereby determining the control strategy of the active curtain wall control system. This strategy fully considers the specific impact of the continuous and complex morphological changes generated by the active curtain wall on the actual performance of the photovoltaic panels distributed on its surface. Therefore, it avoids the waste of solar energy resources caused by existing control methods, as well as the problem of soaring air conditioning energy consumption caused by improper deformation. Attached Figure Description

[0034] Figure 1 This is the overall flowchart of this application;

[0035] Figure 2 This is a schematic diagram of the implementation of this application. Figure 1 ;

[0036] Figure 3 This is a schematic diagram of the implementation of this application. Figure 2 . Detailed Implementation

[0037] It should be noted that, where there is no conflict, the various embodiments disclosed in this application can be combined with each other.

[0038] Specific Implementation Method 1: The photovoltaic efficiency simulation evaluation and optimization method for variable building skin described in this implementation method includes the following steps:

[0039] Step 1: Establish a model of the urban environment and urban shading, and a parametric model of the variable building skin system;

[0040] Step 2: Define the evaluation criteria for assessing variable building skins;

[0041] Step 3: Determine the engineering constraint boundary conditions based on the urban environment and urban shading model, and use the parametric model of the variable building skin system to evolve and simulate the changes in building surface morphology sample data within the engineering constraint boundary conditions. Then, combine the evaluation index as the core objective function to iterate the three-dimensional morphological parameters of each building curtain wall unit to obtain the optimal time-sharing morphological change logic of the variable building skin, and use this logic as the variable skin control strategy.

[0042] Step 1: Establish an environmental model and a parametric model of the variable building skin system.

[0043] First, using meteorological data and the three-dimensional features of urban physical space, a high-precision building environment and urban shading model is established in the Rhino-Grasshopper simulation platform. Second, based on the parametric digital design platform, a three-dimensional solid model of a variable building skin system is constructed, which includes the morphological changes of standard layers and the logic of continuous physical deformation between layers. This enables the model system to accurately respond to the dynamic input of various external environmental parameters and to map the three-dimensional deformation law of the curtain wall geometric units in real time.

[0044] Step two: Calculate evaluation indicators. Three core indicators are proposed and established for systematically evaluating the photovoltaic efficiency and additional energy costs of variable building skins. This invention uniquely establishes four key quantitative indicators for comprehensively evaluating the performance of variable skins, specifically including: photovoltaic energy efficiency (assessing the impact of dynamic morphological changes on the total solar radiation received by the building's overall surface), photovoltaic economic efficiency (assessing the input-output benefits per unit area of ​​the effective photovoltaic installation area after considering installation thresholds), and shape-photovoltaic loss ratio (assessing the dynamic balance between the increase in heating and cooling loads caused by changes in the building's shape coefficient and relative compactness due to continuous morphological changes and the energy gained from photovoltaics).

[0045] Step 3: Assisted control decision-making based on multi-objective optimization algorithms. The parametric model from Step 1 automatically evolves and simulates within the set engineering constraints, generating a massive dataset of building surface morphology changes. Subsequently, combining the four evaluation indicators proposed in Step 2 as the core objective function, a multi-objective optimization software module is used to perform high-frequency real-time optimization iterations on the three-dimensional morphological parameters of each building curtain wall unit. Based on the Pareto front solution set generated from the optimization results, the optimal time-sharing morphological change logic of the variable building skin under this specific light and climate environment is determined, and this logic is extracted and used as a new dimension control strategy to guide the actual actions of the variable skin.

[0046] Step one is as follows:

[0047] Step 1.1: Establishing an Environmental Model. The accuracy of building performance simulation assessment is highly dependent on the granularity of the environmental context. In this step, the building environment analysis must simultaneously cover natural meteorological conditions and urban micro-physical conditions. Specifically, the natural condition information includes the climate zones of the target area, hourly temperatures throughout the year, dry / wet bulb temperatures, precipitation probability, solar radiation intensity, and solar trajectory in different seasons. These key meteorological conditions can be directly obtained from authoritative standard EnergyPlus weather files (.epw format, a standard meteorological data file format widely used for building energy consumption simulation). On the other hand, the impact of the urban micro-environment on the photovoltaic efficiency of building surfaces is mainly and directly reflected in the physical shading effect of surrounding building clusters or natural terrain on direct sunlight and diffused sunlight. When constructing the urban environment model, this invention collects and parameterizes site characteristics such as the ratio of building height to street width, the depth and width of surrounding buildings, building spacing, and plot ratio. These factors are identified as the most critical urban factors affecting the attenuation of illuminance and uneven shadow distribution on the high-rise facades of the target building. Taking Harbin as an example, typical street data of Harbin were collected to construct an urban environment model around the research object. The distribution of high-rise buildings in Harbin is relatively concentrated, with 77% of them showing a scattered cluster layout, and the terrain outline is mostly rectangular. Therefore, the building layout adopted for the simulated plot is a rectangular scattered layout, with high-rise buildings mainly having 20-30 floors, a plot size of 100m×100m, and a distance of 35-65m between the center of the buildings.

[0048] Step 1.2: Establish a parametric model of the variable building skin system. The complex, continuous morphological changes of the building curtain wall units are mathematically reduced and geometrically abstracted. Taking the most common square curtain wall unit as an example, three independent rotation amplitude parameters are defined for each parametric variable unit in a three-dimensional Cartesian coordinate system: RX (rotation around the X-axis), RY (rotation around the Y-axis), and RZ (rotation around the Z-axis). For a simple square unit, with dimensions of 1.2m x 1.2m and a rotation angle of -30° to +30°, the three-axis rotation amplitudes RX, RY, and RZ are defined for each unit. The building has a base area of ​​2500㎡, a floor height of 3.9m, and 40 floors. To achieve the transition from static drawings to dynamic simulation, this model is entirely built on the Grasshopper visual node programming plugin of the Rhino 3D modeling platform. This platform's powerful computational network enables seamless transfer of parametric logic, real-time geometric adjustment, and batch modeling. The illumination calculation and thermal radiation simulation are seamlessly integrated and based on the Ladybug environmental photothermal analysis plugin engine embedded in the Grasshopper platform to perform accurate physical calculations.

[0049] Step two is as follows:

[0050] Step 2.1: Calculate photovoltaic energy efficiency. The photovoltaic energy efficiency studied in this invention refers to the solar energy that a photovoltaic system can capture, affected by changes in the shape of a building's facade. For a single building entity, under ideal conditions without considering internal electrical losses, the absolute value of the total annual solar radiation can be used for macroscopic evaluation. Therefore, the photovoltaic energy efficiency index is proposed to evaluate the overall photovoltaic energy capture capacity of a building after changes in its overall facade shape. Its mathematical formula is as follows:

[0051] ,

[0052] in:

[0053] Photovoltaic energy efficiency of buildings with variable shapes;

[0054] Total annual solar radiation in the area selected for buildings with varying shapes;

[0055] Total annual solar radiation in the selected area for standard-shaped buildings;

[0056] Step 2.2: Calculate the economic efficiency of photovoltaics. The application of building-integrated photovoltaics (BIPV) needs to consider cost; simply expanding the photovoltaic area and deploying low-efficiency photovoltaic equipment is not advisable. Therefore, the economic efficiency of photovoltaics is evaluated using the total annual solar radiation per unit area of ​​the selected area. Since some areas, such as the north-facing facade of a building, have low annual solar radiation, they are unsuitable for installing photovoltaic modules. Considering the economic rationality of photovoltaic system deployment, areas on the building facade with annual solar radiation per unit area exceeding a threshold are selected as installation areas. In 2022, the optimal annual total irradiance for solar photovoltaic power generation on a sloping surface in my country was approximately 1815.8 kWh / m², and the national average annual total irradiance on a flat surface was approximately 1563.4 kWh / m². Based on this, the selection mechanism is set at units where more than half of the area has an annual average total irradiance exceeding 1600 kWh / m². The formula for calculating the economic efficiency of photovoltaics is defined as:

[0057] ,

[0058] in:

[0059] Photovoltaic economic efficiency of buildings with variable shapes;

[0060] Total annual solar radiation in the area selected for buildings with varying shapes;

[0061] Total annual solar radiation in the selected area for standard-shaped buildings;

[0062] Area of ​​the variable-shape building selection area;

[0063] Area of ​​the standard-shaped building selection area;

[0064] Step 2.3: Calculate the shape-photovoltaic loss ratio. Changes in the shape of a building's curtain wall can lead to changes in the building's surface area, thus affecting other building energy performance attributes such as the shape coefficient and radiative heat loss. In building energy consumption calculations, this mainly manifests as an increase in heating and cooling energy consumption. According to previous research, the total heating and cooling energy consumption of a building is linearly negatively correlated with the building's relative shape coefficient (RC). Therefore, the relative shape coefficient can be used to measure the direct impact of shape changes on the building's energy effect, avoiding local optima problems caused by maximizing photovoltaic potential in calculations. Therefore, the formula for calculating the total heating and cooling energy consumption of an office building can be written as:

[0065] ,

[0066] In the formula and It is a constant controlled by other building and environmental factors.

[0067] The relative compactness (RC), also known as the relative volume factor, is calculated by first determining the ratio of a building's volume V to its surface area A (V / A), and then calculating the ratio of the volume V to the surface area Ar of the most compact shape with the same volume (V / Ar). The ratio of these two values ​​is the RC, and its formula is as follows:

[0068] ,

[0069] in:

[0070] Relative compactness;

[0071] Building volume;

[0072] Building surface area;

[0073] The surface area of ​​the most compact shape with the same volume as the building under study.

[0074] Because most buildings in reality are orthogonal polyhedral shapes, it is reasonable to use a cube (the most compact polyhedron) as the most compact reference shape. The RC calculation formula with the cube as the most compact reference shape is:

[0075] ,

[0076] Meanwhile, considering that the purpose of this study is to measure the photovoltaic efficiency of building facades, the concept of shape-photovoltaic loss ratio (K) is proposed. This ratio is the increase in energy consumption caused by the deviation of the building's shape from a standard cube due to changes in its facade shape, and its photovoltaic production capacity. It can represent the comprehensive impact of changes in building facade shape on the building's energy effect and photovoltaic efficiency.

[0077] During the process of the rate of change from 0 to 1, there is always an energy loss due to its shape.

[0078] ,

[0079] in:

[0080] Shape-photovoltaic loss ratio of buildings with variable forms;

[0081] Annual heating and cooling energy consumption of buildings with varying shapes;

[0082] Annual heating and cooling energy consumption of standard-shaped buildings;

[0083] Total annual solar radiation in the area selected for buildings with varying shapes;

[0084] Total annual solar radiation in the screening area for standard-shaped buildings;

[0085] Annual heating and cooling energy consumption of a standard cubic building;

[0086] Based on the above formulas, the formula for calculating the body shape-photovoltaic loss ratio can be summarized as follows:

[0087] ,

[0088] in:

[0089] Shape-photovoltaic loss ratio of buildings with variable forms;

[0090] Total annual solar radiation in the area selected for buildings with varying shapes;

[0091] Total annual solar radiation in the screening area for standard-shaped buildings;

[0092] Changing the shape and volume of buildings;

[0093] Standard building volume;

[0094] Surface area of ​​buildings with varying shapes;

[0095] Surface area of ​​standard-shaped buildings;

[0096] The calculated shape-photovoltaic loss ratio represents the ratio of the additional energy consumption caused by the building shape with a changed skin shape to the photovoltaic energy production share of the standard skin shape relative to the standard cube. A ratio greater than 1 means that the additional energy consumption caused by the change in skin shape accounts for a larger share of the photovoltaic energy production share than that of the standard skin shape.

[0097] Step three specifically involves the execution process of multi-objective optimization:

[0098] Step 3.1: Set optimization objectives. Set the calculated photovoltaic energy efficiency and photovoltaic economic efficiency as the fitness objective functions that the algorithm needs to maximize; at the same time, set the size-photovoltaic depreciation ratio as the fitness objective function that needs to be strictly minimized.

[0099] Step 3.2: Use a parametric modeling platform to simulate and generate massive amounts of morphological change sample data. Extract and analyze features from the large amount of simulated data. Use multi-objective optimization software (such as the Octopus plugin environment on the Grasshopper platform, based on the principle of evolutionary algorithm) to perform automated real-time morphological optimization of the continuous three-axis rotation angle of each curtain wall unit.

[0100] Step 3.3: Output Decision Dimensions. Based on the Pareto optimal solution set formed after multiple generations of genetic evolution by the multi-objective optimization tool, decision-makers can select the optimal skin morphology parameters that achieve a perfect compromise among various indicators under different seasons and climatic conditions. This result is converted into digital control signals and superimposed on the existing automated control system of the variable building curtain wall.

[0101] This application establishes a typical physical model of a variable building skin for integrated photovoltaic performance evaluation. This application breaks through the limitations of traditional static building curtain wall photovoltaic evaluation, and for the first time deeply integrates the dynamic geometric evolution logic of the building skin with parametric design. This enables precise physical illumination and thermodynamic coupling simulation modeling of complex moving components, providing a solid three-dimensional digital twin foundation for subsequent data analysis.

[0102] This application innovatively establishes three comprehensive and multi-dimensional evaluation indicators. By integrating photovoltaic energy efficiency, photovoltaic economic efficiency, and the form-to-photovoltaic loss ratio, this application not only considers the absolute production capacity and economic cost-effectiveness of photovoltaic power generation panels, but also uses an innovative loss ratio coefficient to strictly constrain the increase in heat dissipation caused by changes in building facade shape, and limits the electromechanical drive energy consumption during frequent physical deformation processes. This rigorous indicator matrix ensures the scientific nature, completeness, and closed-loop nature of the evaluation system.

[0103] This application proposes a unified and highly standardized closed-loop workflow of "modeling-evaluation-optimization". This workflow has strong system universality and cross-regional generalization ability, and can quickly transfer and deploy models, perform adaptive simulation calculations and localization assessments for different latitudes, different climate zones and different urban light environment conditions (such as frigid regions, hot summer and cold winter regions).

[0104] Based on the output of the evaluation system, a clear and data-driven approach to optimize the facade condition was established. Through an embedded multi-objective genetic optimization algorithm, the complex curtain wall form design process, which originally relied heavily on the subjective experience and judgment of architects and facade engineers, was transformed into an automatic performance optimization process based entirely on objective operational data. This allows the computer to quickly lock in the optimal compromise form for multiple objectives from a vast parameter solution space.

[0105] This application provides a completely new digital control decision-making dimension for the underlying control logic of variable building skins. Traditional active variable curtain walls often use only a single logic basis for driving panel rotation, such as "indoor anti-glare shading" or "visual transparency." This application seamlessly integrates the optimization of photovoltaic efficiency throughout its entire life cycle as a new high-level instruction dimension, truly achieving a perfect unity between the self-regulation of the microclimate of modern buildings and the self-sufficiency of renewable energy production capacity.

[0106] Figure 2 In this embodiment of the application, a variable building skin parametric unit logic framework is established based on the Grasshopper platform according to the natural environment and meteorological data of the target city, as well as the generation module of the system when the execution unit continuously scales, translates and rotates. Figure 3 In this embodiment of the application, after the four calculated evaluation indicators are imported into the Octopus multi-objective optimizer, the genetic algorithm undergoes multiple generations of breeding iterations and gradually converges, finally generating an auxiliary control decision output diagram of the optimal solution set of the three-dimensional Pareto Front.

[0107] It should be noted that the specific embodiments are merely explanations and illustrations of the technical solution of the present invention and should not be used to limit the scope of protection. Any modifications made in accordance with the claims and specification of the present invention that are only partial should still fall within the protection scope of the present invention.

Claims

1. A method for simulation evaluation and optimization of photovoltaic efficiency of variable building skin, characterized in that... Includes the following steps: Step 1: Establish a model of the urban environment and urban shading, and a parametric model of the variable building skin system; Step 2: Define the evaluation criteria for assessing variable building skins; Step 3: Determine the engineering constraint boundary conditions based on the urban environment and urban shading model, and use the parametric model of the variable building skin system to evolve and simulate the changes in building surface morphology sample data within the engineering constraint boundary conditions. Then, combine the evaluation index as the core objective function to iterate the three-dimensional morphological parameters of each building curtain wall unit to obtain the optimal time-sharing morphological change logic of the variable building skin, and use this logic as the variable skin control strategy.

2. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 1, characterized in that... The specific steps of step 1 are as follows: Step 11: Obtain natural condition information, collect and parameterize land parcel features, and then use the natural condition information and land parcel features to establish an urban environment and urban shading model; Step 12: Use the Rhino 3D modeling platform to construct a parametric model of the variable building skin system that includes the morphological changes of standard layers and the logic of continuous physical deformation between layers.

3. The method for simulation evaluation and optimization of photovoltaic efficiency of a variable building skin according to claim 2, characterized in that... The natural condition information includes the climate zones of the target region, hourly temperatures throughout the year, dry / wet bulb temperatures, precipitation probability, solar radiation intensity, and solar trajectory in different seasons.

4. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 3, characterized in that... The characteristics of the plot include the ratio of building height to street width, the depth and width of surrounding buildings, the distance between buildings, and the plot ratio.

5. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 4, characterized in that... The evaluation metrics used in step 2 to assess the variable building skin include photovoltaic energy efficiency, photovoltaic economic efficiency, and the shape-to-photovoltaic loss ratio.

6. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 5, characterized in that... The photovoltaic energy efficiency is expressed as: ， in, Photovoltaic energy efficiency for buildings with variable shapes The total annual solar radiation for the area selected for buildings with varying shapes. The total annual solar radiation for the selected area of ​​standard-shaped buildings.

7. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 6, characterized in that... The photovoltaic economic efficiency is expressed as: ， in, To improve the economic efficiency of photovoltaics in buildings with variable shapes. The total annual solar radiation for the area selected for buildings with varying shapes. The total annual solar radiation for the area selected for standard-shaped buildings. Selecting the area for buildings with varying shapes. Select the area for standard-shaped buildings.

8. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 7, characterized in that... The shape-photovoltaic loss ratio is expressed as: ， in, For the shape-photovoltaic loss ratio of buildings with variable forms, The total annual solar radiation for the area selected for buildings with varying shapes. The total annual solar radiation for the area selected for standard-shaped buildings. To change the shape and volume of the building, For standard-shaped building volume, To vary the surface area of ​​the building's shape. The surface area of ​​a standard-shaped building.

9. The photovoltaic efficiency simulation evaluation and optimization method for a variable building skin according to claim 8, characterized in that... The specific steps of step 3 are as follows: Step 31: Maximize the photovoltaic energy efficiency and photovoltaic economic efficiency as fitness objective functions, and minimize the size-photovoltaic depreciation ratio as fitness objective functions. Step 32: Determine the engineering constraint boundary conditions based on the urban environment and urban shading model, and use the parametric model of the variable building skin system to evolve within the engineering constraint boundary conditions and simulate and generate sample data of building surface morphology changes; Step 33: Based on the morphological change sample data, extract the distribution characteristics of the parameters, and based on the fitness objective function in Step 31, iterate the three-dimensional morphological parameters of each building curtain wall unit to obtain the optimal time-sharing morphological change logic of the variable building skin, and use this logic as the variable skin control strategy.

10. The method for simulation evaluation and optimization of photovoltaic efficiency of a variable building skin according to claim 9, characterized in that... In step 33, morphological optimization is performed using the Octopus plugin environment on the Grasshopper platform.

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