Yang Chunyuan, Yu Siyao, Cao Yi, Abdolhosseinzadeh Sama
College of Culture and Tourism, Qujing Normal University, Qujing 655011, Yunnan, China.
College of Design and Engineering, National University of Singapore, 21 Lower Kent Ridge Road, Singapore 119077, Singapore.
Heliyon. 2023 Dec 7;10(1):e23387. doi: 10.1016/j.heliyon.2023.e23387. eCollection 2024 Jan 15.
This study focuses on designing sustainable buildings with a specific emphasis on reducing energy consumption and optimizing costs. To address the time-consuming nature of simulation software like TRNSYS and Energy Plus, a novel meta-heuristic optimization algorithm called the Developed Optimization Algorithm of Farmland Fertility (DFFA) is provided. The DFFA algorithm is utilized to optimize parameters related to the building envelope, encompassing walls, windows, and glass curtain walls, aiming to minimize energy demand and construction expenses. Comparative analysis with other approaches such as EPO, LOA, MVO, and FFA demonstrates significant reductions in energy consumption and building design costs achieved by employing the proposed algorithm. Furthermore, the DFFA algorithm yields the desired results within fewer iterations. By increasing the surface area of the glass curtain wall and total window space, improvements in natural ventilation and interior lighting are observed. Despite similar window opening measurements across the compared methods, the suggested algorithm surpasses others when it comes to overall cost and energy efficiency. The total cost reduction compared to the initial design amounts to 39 %. Thus, the DFFA algorithm proves to be more effective in conserving energy in buildings compared to other analyzed procedures. This research serves as a case study and presents a promising method applicable to designing various building types under different weather conditions in future projects.
本研究着重于设计可持续建筑,特别强调降低能源消耗并优化成本。为解决诸如TRNSYS和Energy Plus等模拟软件耗时的问题,提供了一种名为农田肥力改进优化算法(DFFA)的新型元启发式优化算法。DFFA算法用于优化与建筑围护结构相关的参数,包括墙体、窗户和玻璃幕墙,旨在将能源需求和建设成本降至最低。与其他方法(如EPO、LOA、MVO和FFA)的对比分析表明,采用所提算法可显著降低能源消耗和建筑设计成本。此外,DFFA算法在较少的迭代次数内就能产生预期结果。通过增加玻璃幕墙的表面积和总窗面积,可观察到自然通风和室内采光得到改善。尽管在比较的方法中窗户开启尺寸相似,但在所提算法在总体成本和能源效率方面优于其他算法。与初始设计相比,总成本降低了39%。因此,与其他分析方法相比,DFFA算法在建筑节能方面更有效。本研究作为一个案例研究,提出了一种在未来项目中适用于在不同天气条件下设计各种建筑类型的有前景的方法。