Topographical optimisation of single-storey non-domestic steel framed buildings using photovoltaic panels for net-zero carbon impact

被引:18
作者
McKinstray, Ross [1 ]
Lim, James B. P. [1 ]
Tanyimboh, Tiku T. [2 ]
Phan, Duoc T. [3 ]
Sha, Wei [1 ]
Brownlee, Alexander E. I. [4 ]
机构
[1] Queens Univ Belfast, SPACE, David Keir Bldg, Belfast BT9 5AG, Antrim, North Ireland
[2] Univ Strathclyde, Dept Civil & Environm Engn, Glasgow G1 1XJ, Lanark, Scotland
[3] Curtin Univ Sarawak, FES, Dept Civil & Construct Engn, Miri 98009, Malaysia
[4] Univ Stirling, Div Comp Sci & Math, Stirling FK9 4LA, Scotland
关键词
Portal frames; Genetic algorithms; Artificial neural network; Optimization; Energy efficiency; DESIGN OPTIMIZATION; GENETIC ALGORITHMS;
D O I
10.1016/j.buildenv.2014.12.017
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A methodology is presented that combines a multi-objective evolutionary algorithm and artificial neural networks to optimise single-storey steel commercial buildings for net-zero carbon impact. Both symmetric and asymmetric geometries are considered in conjunction with regulated, unregulated and embodied carbon. Offsetting is achieved through photovoltaic (PV) panels integrated into the roof. Asymmetric geometries can increase the south facing surface area and consequently allow for improved PV energy production. An exemplar carbon and energy breakdown of a retail unit located in Belfast UK with a south facing PV roof is considered. It was found in most cases that regulated energy offsetting can be achieved with symmetric geometries. However, asymmetric geometries were necessary to account for the unregulated and embodied carbon. For buildings where the volume is large due to high eaves, carbon offsetting became increasingly more difficult, and not possible in certain cases. The use of asymmetric geometries was found to allow for lower embodied energy structures with similar carbon performance to symmetrical structures. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:120 / 131
页数:12
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