Energy and Buildings, Vol.158, 1189-1205, 2018
An integrated BIM-based framework for the optimization of the trade-off between embodied and operational energy
Design choices with a unilateral focus on the reduction of operational energy for developing energy efficient and near-zero energy building practices can increase the impact of the embodied energy, as there is a trade-off between embodied and operational energy. Multi-objective optimization approaches enable exploration of the trade-off problems to find sustainable design strategies, but there has been limited research in applying it to find optimal design solution(s) considering the embodied versus operational energy trade-off. Additionally, integration of this approach into a Building Information Modeling (BIM) for facilitating set up of the building model toward optimization and utilizing the benefits of BIM for sharing information in an interoperable and reusable manner, has been mostly overlooked. To address these issues, this paper presents a framework that supports the making of appropriate design decisions by solving the trade-off problem between embodied and operational energy through the integration of a multi-objective optimization approach with a BIM-driven design process. The applicability of the framework was tested by developing a prototype and using it in a case study of a low energy dwelling in Sweden, which showed the potential for reducing the building's Life Cycle Energy (LCE) use by accounting for the embodied versus operational energy trade-off to find optimal design solution(s). In general, the results of the case study demonstrated that in a low energy dwelling, depending on the site location, small reductions in operational energy (i.e. 140 GJ) could result in larger increases in embodied energy (i.e. 340 GJ) and the optimization process could yield up to 108 GJ of LCE savings relative to the initial design. This energy saving was equivalent to up to 8 years of the initial design's operational energy use for the dwelling, excluding household electricity use. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:Building information modeling;Design;Embodied energy;Genetic algorithm;Life cycle energy;Multi-objective optimization;Operational energy;Trade-off