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

Ross McKinstray, James B. P. Lim, Tiku T. Tanyimboh, Duoc T. Phan, Wei Sha, Alexander E. L. Brownlee

    Research output: Contribution to journalArticle

    14 Citations (Scopus)
    315 Downloads (Pure)

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)120–131
    Number of pages12
    JournalBuilding and Environment
    Volume86
    Early online date27 Dec 2014
    DOIs
    Publication statusPublished - Apr 2015

    Keywords

    • Portal frames
    • Genetic algorithms
    • Artificial neural network
    • Optimization
    • Energy efficiency

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