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Optimum design of a house and its HVAC systems using simulation-based optimisation

机译:使用基于仿真的优化对房屋及其HVAC系统进行优化设计

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This paper deals with a multi-objective optimisation problem where the objective is to minimise CO_2-eq emissions and investment cost of a multi-zone single-family house and its heating/cooling systems. Eight design variables are subjected to study: level of building tightness, insulation thickness of the external wall, floor and roof, type of window. glazing, window shading, heat recovery and heating/ cooling systems. Simulation-based optimisation is implemented to minimise the objective functions by finding optimum values of the design variables. This is done by combining the dynamic building performance simulation program IDA-ICE 3.0 with a modified genetic algorithm. The optimisation results give the optimal solutions for the problem in the form of a Pareto front, showing the trade-off between the two objectives. The obtained solutions are much better than the initial designs of the house in terms of lower CO_2-eq emissions and investment cost. It is noted from the obtained results that the significance of the heating system is higher than the other design variables so that the optimal solutions can be classified according to the type of the heating system. It is also noted that there is a need to include a thermal comfort criterion as a problem constraint to limit overheating hours during summer.
机译:本文研究了一个多目标优化问题,目标是使多区域单户住宅及其供暖/制冷系统的CO_2当量排放量和投资成本最小化。研究了八个设计变量:建筑物的密封性水平,外墙,地板和屋顶的隔热厚度,窗户的类型。玻璃,遮阳,热回收和加热/冷却系统。实现基于仿真的优化,以通过找到设计变量的最佳值来最小化目标函数。这是通过将动态建筑性能模拟程序IDA-ICE 3.0与改进的遗传算法相结合来完成的。优化结果以帕累托前沿的形式给出了问题的最佳解决方案,表明了两个目标之间的权衡。就较低的CO_2当量排放量和投资成本而言,所获得的解决方案比房屋的最初设计要好得多。从获得的结果中可以看出,加热系统的重要性高于其他设计变量,因此可以根据加热系统的类型对最佳解决方案进行分类。还应注意,有必要将热舒适度标准作为限制夏季夏季过热时间的问题约束。

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