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首页> 外文期刊>Building and Environment >Genetic-algorithm based approach to optimize building envelope design for residential buildings
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Genetic-algorithm based approach to optimize building envelope design for residential buildings

机译：基于遗传算法的住宅建筑围护结构优化方法

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摘要

A simulation-optimization tool is developed and applied to optimize building shape and building envelope features. The simulation-optimization tool couples a genetic algorithm to a building energy simulation engine to select optimal values of a comprehensive list of parameters associated with the envelope to minimize energy use for residential buildings. Different building shapes were investigated as part of the envelope optimization, including rectangle, L, T, cross, U, H, and trapezoid. Moreover, building envelope features were considered in the optimization analysis including wall and roof constructions, foundation types, insulation levels, and window types and areas. The results of the optimization indicate rectangular and trapezoidal shaped buildings consistently have the best performance (lowest life-cycle cost) across five different climates. It was also found that rectangle and trapezoid exhibit the least variability from best to worst within the shape.
机译：开发了模拟优化工具，并将其应用于优化建筑物形状和建筑物围护结构特征。仿真优化工具将遗传算法耦合到建筑物能源仿真引擎，以选择与围护结构相关的综合参数列表的最佳值，以最大程度地减少住宅建筑物的能耗。作为包络优化的一部分，研究了不同的建筑形状，包括矩形，L，T，十字，U，H和梯形。此外，在优化分析中还考虑了建筑围护结构的特征，包括墙壁和屋顶结构，地基类型，隔热等级以及窗户的类型和面积。优化结果表明，矩形和梯形建筑物在五个不同的气候下始终具有最佳性能（最低生命周期成本）。还发现矩形和梯形在形状内从最佳到最差的变化最小。

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