Metamodels are developed and used for aerodynamic optimization of a ducted opening integrated into a high-rise building to maximize the amplification factor within the duct. The duct consists of a nozzle, a throat, and a diffuser. 211 high-resolution 3D RANS CFD simulations are performed to generate training and testing datasets. The space-filling design and Genetic algorithm are used for data sampling and optimization, respectively. The performance of five commonly-used metamodels is systematically investigated: Response Surface Methodology (RSM), Kriging (KG), Neural Network (NN), Support Vector Regression (SVR), and Genetic Aggregation Response Surface (GARS). The investigation is based on (i) detailed in-sample and out-of-sample evaluations of the metamodels, (ii) annual available power in the wind (P_available), and (iii) annual energy production (AEP) for a 3-bladed horizontal-axis wind turbine (HAWT) installed in the mid-throat for the optimum designs obtained by the metamodels. The results show that converging-diverging ducted openings can magnify the experienced wind speed by the turbine and enhance the available wind power. In addition, the use of different metamodels can lead to a variation of up to 153% in the estimated P_available. For a small dataset, crude yet still acceptable accuracy can be achieved for Genetic Aggregation Response Surface and Kriging at a very low computational time.

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Building integrated photovoltaic (BIPV) applications are key to increase the share of renewable energy in the built environment. A large potential for BIPV deployment is related to building facades. The assessment of BIPV facades depends on the accurate modelling of exterior convective heat transfer coefficients (eCHTC). However, eCHTC models commonly used in BIPV modelling tend to be simplified. This paper proposes a simulation framework that combines detailed computational fluid dynamics with a multi-physics BIPV model to investigate the influence of eCHTC on the performance of BIPV facades (cell temperature and power). The evaluation is performed for different building geometries, wind speeds, wind directions, solar irradiations, and ambient temperatures. The results show that local variations in eCHTC can cause variations in cell temperature up to 42 °C between the BIPV modules across the facade. These temperature differences are associated with differences in power up to 17% across the BIPV facade. In general, lower temperatures (and higher power output) occur near the edges of the facade while higher temperatures (and lower power output) occur at the middle and at the bottom of the facade. Therefore, a detailed assessment of wind effects is recommended in order to verify the local operating conditions of the BIPV modules. The framework and findings presented in this work are relevant for applications in which the knowledge of the local behaviour is important, such as degradation studies.@en