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Multi-Objectives Optimization of Ventilation Controllers for Passive Cooling in Residential Buildings

机译:住宅建筑中被动冷却通风控制器的多目标优化

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摘要

An inappropriate indoor climate, mostly indoor temperature, may cause occupants’ discomfort. There are a great number of air conditioning systems that make it possible to maintain the required thermal comfort. Their installation, however, involves high investment costs and high energy demand. The study analyses the possibilities of limiting too high a temperature in residential buildings using passive cooling by means of ventilation with ambient cool air. A fuzzy logic controller whose aim is to control mechanical ventilation has been proposed and optimized. In order to optimize the controller, the modified Multiobjective Evolutionary Algorithm, based on the Strength Pareto Evolutionary Algorithm, has been adopted. The optimization algorithm has been implemented in MATLAB®, which is coupled by MLE+ with EnergyPlus for performing dynamic co-simulation between the programs. The example of a single detached building shows that the occupants’ thermal comfort in a transitional climate may improve significantly owing to mechanical ventilation controlled by the suggested fuzzy logic controller. When the system is connected to the traditional cooling system, it may further bring about a decrease in cooling demand.
机译:不适当的室内气候(主要是室内温度)可能会引起乘客的不适。有许多空调系统可以维持所需的热舒适性。然而,它们的安装涉及高投资成本和高能量需求。该研究分析了通过使用周围冷空气进行通风的被动冷却来限制住宅建筑物中温度过高的可能性。提出并优化了旨在控制机械通风的模糊逻辑控制器。为了优化控制器,采用了基于强度帕累托进化算法的改进多目标进化算法。优化算法已在MATLAB ®中实现,该算法由MLE +与EnergyPlus耦合在一起,用于在程序之间执行动态协同仿真。单个独立建筑的示例显示,由于建议的模糊逻辑控制器控制的机械通风,在过渡气候中居住者的热舒适性可能会大大改善。当系统连接到传统的冷却系统时,可能会进一步降低冷却需求。

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