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Residential building design optimisation using sensitivity analysis and genetic algorithm

机译:基于灵敏度分析和遗传算法的住宅建筑设计优化

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The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation.
机译:本文的目的是将灵敏度分析和基于仿真的优化相结合,以优化阿根廷沿海地区住宅建筑的热能性能。选择了一个实际的房子作为案例研究。这是一栋典型的本地单户住宅,其某些房间仅通过自然通风进行调节,而其他房间则通过机械空调(混合通风)进行自然通风。因此,选择自然通风客厅的总时数和卧室空调的总能耗作为目标函数,以使其最小化。表征房屋热和能源性能的全局目标函数定义为这些目标函数的加权总和。该目标函数是使用EnergyPlus建筑性能模拟程序计算的。然后,我们使用Morris筛选方法进行了敏感性分析,以对设计变量对目标函数的影响进行排名。这表明,在考虑的房屋的给定目标函数中,外墙的类型,窗户的渗透率和太阳方位角是最有影响力的设计变量,而且方位角要么对目标函数具有高度的非线性影响,要么是与其他变量高度相关,在任何情况下都应进行更好的离散化。

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