Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm
Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm
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DOI：
10.3390/buildings10050088
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发表时间：
2020-05
期刊：
影响因子：
3.8
通讯作者：
S. Chaturvedi;Elangovan Rajasekar;S. Natarajan
中科院分区：
文献类型：
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作者：
S. Chaturvedi;Elangovan Rajasekar;S. Natarajan
运营不确定性在确定减少全球南方建筑能源足迹的潜在途径方面发挥着关键作用。本文提出了一种非支配排序遗传算法（NSGA II）的多目标建筑设计优化运行的不确定性。位于中纬度草原和沙漠地区（Koppen气候分类：BSh）在全球南部的住宅楼已被选定为我们的调查。通过13，122种不同的能源效率措施评估了年度建筑能耗和冷却设定值未达到小时数（h）的总数。NSGA II算法确定了6个Pareto最优解。鲁棒性的Pareto解决方案进行了评估，通过比较他们的性能灵敏度超过162个不确定的操作场景。最佳的能源效率措施的最终选择是通过制定一个强大的多标准决策功能，将性能，用户偏好和可靠性标准。从这个强大的方法得到的结果进行了比较，使用确定性的方法。与基本情况相比，最优化的能源效率措施导致年能耗降低9.24%，冷却设定值未满足h的数量降低45%。
Operational uncertainties play a critical role in determining potential pathways to reduce the building energy footprint in the Global South. This paper presents the application of a non-dominated sorting genetic (NSGA II) algorithm for multi-objective building design optimization under operational uncertainties. A residential building situated in a mid-latitude steppe and desert region (Koppen climate classification: BSh) in the Global South has been selected for our investigation. The annual building energy consumption and the total number of cooling setpoint unmet hours (h) were assessed over 13,122 different energy efficiency measures. Six Pareto optimal solutions were identified by the NSGA II algorithm. Robustness of Pareto solutions was evaluated by comparing their performance sensitivity over 162 uncertain operational scenarios. The final selection for the most optimal energy efficiency measure was achieved by formulating a robust multi-criteria decision function by incorporating performance, user preference, and reliability criteria. Results from this robust approach were compared with those obtained using a deterministic approach. The most optimal energy efficiency measure resulted in 9.24% lower annual energy consumption and a 45% lower number of cooling setpoint unmet h as compared to the base case.