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Optimization on ACC Systems and Layout Design for Maximizing Thermal Comfort and Energy Saving in Large Rooms - A Case Study

机译:优化ACC系统和布局设计以最大程度地提高大房间的热舒适性和节能效果-案例研究

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A public room in buildings could hold a number of persons who may prefer dissimilar thermal environment. Different areas in such rooms may have different temperatures. Facility layout in such a room has effect on the distribution of the people in the room, thus it may affect its thermal environment. It is meaningful and challenging to effectively operate an air-conditioning control (ACC) system by taking the above mentioned factors into account such that the thermal environment is improved and energy is saved. This work aims at optimally operating an ACC system and designing the facility layout so as to maximize the total thermal satisfaction rate (TSR) as well as energy saving. To do so, with a large library room at Macau University of Science and Technology (MUST) as a case scenario, an investigation with a large number of experiments is conducted to collect necessary data. Based on the data, regression analysis is done to predict its indoor temperatures in different areas and TSR at a given temperature. Then, we propose a particle swarm optimization (PSO) algorithm such that an optimal or near-optimal solution can be efficiently found. By numerical results, it is observed that the proposed method can significantly improve the total TSR and save energy.
机译:建筑物中的公共房间可以容纳许多可能喜欢不同热环境的人。在这些房间的不同区域可能会有不同的温度。在这样的房间中布置设施会影响房间中人员的分布,因此可能会影响其热环境。通过考虑上述因素,从而改善热环境并节省能源,有效地操作空调控制(ACC)系统是有意义且具有挑战性的。这项工作旨在优化ACC系统的运行并设计设施布局,以最大程度地提高总热满意度(TSR)并节省能源。为此,以澳门科技大学(MUST)的一间宽敞的图书室为例,进行了大量实验研究以收集必要的数据。根据数据,进行回归分析以预测其在不同区域的室内温度以及给定温度下的TSR。然后,我们提出了一种粒子群优化(PSO)算法,以便可以有效地找到最优或接近最优的解决方案。从数值结果可以看出,该方法可以显着提高总TSR并节省能源。

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