4.7 Article

A multi-objective optimization framework for building-integrated PV envelope design balancing energy and cost

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 342, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2022.130930

Keywords

Building-integrated photovoltaics (BIPV); Building envelope design; Multi-objective optimization (MOO); Energy; Cost

Funding

  1. 'BIPV Enabler' research project - Commercialization of R&D Funding Initiative Pilot at the Australia Renewable Energy Agency
  2. EOF scheme at RMIT University

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This study introduces a multi-objective optimization framework to optimize life cycle energy and life cycle cost simultaneously, considering different types of BIPV applications. The framework includes a set of design variables such as tilt angle, window-to-wall ratio, PV placement and PV product type, and can generate a set of the best BIPV design alternatives.
The design of building-integrated photovoltaic (BIPV) envelopes involves a large set of envelope-related pa-rameters, PV-related parameters and conflicting performance criteria. Therefore, optimization of BIPV design is crucial and it has become a complex process. Existing BIPV design optimization frameworks lack BIPV product and application type-related variables, and most studies cannot handle large sets of design variables and auto-matically generate a set of alternative optimal designs. Therefore, an optimization framework has become a major requirement in BIPV envelope design. This study introduces a multi-objective optimization (MOO) framework to optimize life cycle energy (LCE) and life cycle cost (LCC) simultaneously, at the conceptual BIPV envelope design stage, considering different BIPV application types for the selection of appropriate BIPV prod-ucts and designs. A set of envelope design features, as well as PV-related features such as tilt angle, window-to-wall ratio (WWR), PV placement and PV product type, are included as design variables in the framework. The novelty of this study is that it generates a set of the best BIPV design alternatives based on multiple objectives, PV products and building features. Alternative designs include the best building surface features and the best BIPV product for a given performance criterion. The framework is demonstrated using canopy, roof sheet and cladding BIPV applications and the results incorporate different design solutions for each case study. The results show that MOO is operational for early BIPV design decisions based on technical considerations of energy and cost. Mid-design stage decisions can be guided by these simulated results but are not sufficient to define design de-cisions. Client subjectivity, taste and preference may heavily impact the feasibility of applying the optimization results, because in some cases, energy optimization is not the overarching goal of the client.

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