Multi-objective optimisation framework for designing office windows : quality of view, daylight and energy efficiency

Pilechiha, Peiman and Mahdavinejad, Mohammadjavad and Pour Rahimian, Farzad and Carnemollad, Phillippa and Seyedzadeh, Saleh (2020) Multi-objective optimisation framework for designing office windows : quality of view, daylight and energy efficiency. Applied Energy, 261. 114356. ISSN 0306-2619

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    This paper presents a new, multi-objective method of analysing and optimising the energy processes associated with window system design in office buildings. The simultaneous consideration of multiple and conflicting design objectives can make the architectural design process more complicated. This study is based on the fundamental recognition that optimising parameters on the building energy loads via window system design can reduce the quality of the view to outside and the received daylight – both qualities highly valued by building occupants. This paper proposes an approach for quantifying Quality of View in office buildings in balance with energy performance and daylighting, thus enabling an optimisation framework for office window design. The study builds on previous research by developing a multi-objective method of assessment of a reference room which is parametrically modelled using actual climate data. A method of Pareto Frontier and a weighting sum is applied for multi-objective optimisation to determine best outcomes that balance design requirements. The Results reveal the maximum possible window to wall ratio for the reference room. The optimisation model indicates that the room geometry should be altered to achieve the lighting and view requirements set out in building performance standards. The research results emphasise the need for window system configuration to be considered in the early design stages. This exploratory approach to a methodology and framework considers both building parameters and the local climate condition. It has the potential to be adopted and further refined by other researchers and designers to support complex, multi-factorial design decision-making.

    ORCID iDs

    Pilechiha, Peiman, Mahdavinejad, Mohammadjavad, Pour Rahimian, Farzad, Carnemollad, Phillippa and Seyedzadeh, Saleh ORCID logoORCID:;