Multi-objective optimisation for building integrated photovoltaics (BIPV) roof projects in early design phase. (1st March 2022)

• Record Type: Journal Article
• Authors: Wijeratne, W.M. Pabasara Upalakshi; Samarasinghalage, Tharushi Imalka; Yang, Rebecca Jing; Wakefield, Ron
• Is Part Of: Applied energy. Volume 309(2022)
• Publication Date: 2022-03-01
• Subjects: Multi-objective design optimization -- Building-integrated photovoltaics -- Early design phase -- Life cycle cost -- Life cycle energy; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2021.118476
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: BIPV roof sheet and skylight applications need to be explored in the early design stage. A method for multi objective optimisation of roof sheet and skylight BIPV application is proposed. Application of multi objective optimisation method to a case study with roof sheets and skylights. The multi objective optimisation method simplifies identification of feasible BIPV roof designs in the early design phase. Abstract: Building-integrated photovoltaics (BIPV) is an excellent renewable energy application for building envelopes. In Australia, BIPV roofing is considered to be promising because of recent major concerns about fire risks of façades. However, the integration of PV into building envelope elements is a complicated process which, if not done properly, may lead to failure of the BIPV system. Therefore, feasible BIPV design solutions need to be examined in terms of life-cycle cost and energy performance from the early design phase of a BIPV envelope project. There have been few investigations of the identification of feasible BIPV design options in the early design phase to enable product selection and parametric tests. This study explores a multi-objective optimization method which formulates feasible BIPV envelope design options which have relatively high energy generation and low life cycle costs to informed decision making. The optimisation process has four segments: data inputs, simulator, optimizer and pareto front based optimised BIPV solutions. The proposed multi- objective optimization process is applied in a BIPV roof application using a case study in Australia with roof sheets and skylights. The results demonstrate seven optimum roof sheet BIPV design solutions and fourteen optimum skylight BIPV design solutions to enable design makers to compare and select the most appropriate. The life cycle cost, life cycle energy, CO2 emissions avoided, net present value, payback period, and levelized cost of energy of BIPV solutions vary based on the BIPV modules, tilt angles and placement locations. The proposed optimization method is a helpful guide for BIPV design professionals to identify suitable BIPV design options in the early design phase instead of relying on rule-of-thumb experience.