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Assessing the impacts of real-time occupancy state transitions on building heating/cooling loads

机译:评估实时占用状态转换对建筑物供暖/制冷负荷的影响

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Even though it has been widely accepted that occupancy is one of the most important factors impacting energy use of HVAC systems, how occupancy is associated with heating/cooling loads for sustained and maximum energy efficiency in multi-zone buildings is still not well understood. This study analyses the impact of occupancy on heating/cooling loads at the building level using occupancy state transitions. A data-driven approach is developed applying an enhanced Variable Neighborhood Search algorithm to determine setpoint controls for individual zones and to minimize the heating/cooling loads based on occupancy state transitions. Simulations are used to compare the loads after implementing the proposed approach with the baseline control to quantify the impacts. Based on the results, the optimal combinations of setpoint/setback schedules and distances for each zone were identified to minimize heating/cooling loads at the building level. The convergence of the search was not influenced by different occupancy assignments or initial solutions, and there was no random solution that could outperform the proposed approach to reduce heating/cooling loads based on occupancy transitions. A minimum of 10.4% and a maximum of 28.3% load reduction were achieved in the case study building, compared to the baseline control. (C) 2016 Elsevier B.V. All rights reserved.
机译:尽管已经被广泛接受,占用率是影响HVAC系统能源使用的最重要因素之一,但是对于如何在多区域建筑物中实现持续和最大的能源效率,占用率与供暖/制冷负荷之间的关系仍然不甚了解。本研究使用占用状态转换来分析占用对建筑物级别上的供热/制冷负荷的影响。开发了一种数据驱动的方法,该方法应用了增强的可变邻域搜索算法来确定各个区域的设定点控制,并根据占用状态的变化将供暖/制冷负荷降至最低。在实施建议的方法后,将模拟与基线控制进行比较以量化影响。根据结果​​,确定每个区域的设定点/回缩时间表和距离的最佳组合,以最大程度地减少建筑物级别的供暖/制冷负荷。搜索的收敛性不受不同的占用分配或初始解决方案的影响,并且没有随机解决方案可以胜过所提出的基于占用转变的减少供暖/制冷负荷的方法。与基线对照相比,案例研究大楼的最小负载减少了10.4%,最大负载减少了28.3%。 (C)2016 Elsevier B.V.保留所有权利。

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