Multi-objective solar building envelope design optimization
Creators: name: Samarasinghalage, Tharushi
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 330204
subject: Building information modelling and management
classificationCode: 330206
subject: Building science, technologies and systems

description: Of the different sectors which consume energy, the building sector energy consumption is significantly higher and therefore, renewable energy in buildings has recently received the attention of stakeholders of the building industry. Building integrated photovoltaics (BIPV), is a dual-purpose renewable energy source which acts as a building component installed as part of the building envelope. BIPV modules integrated into building envelopes are used in three major application areas namely, roofs, facades, and external devices. There are several BIPV application type subcategories under these major categories such as skylight, roof sheet, rainscreen, curtain wall, double-skin facades, windows, balcony, parapet, canopy and shading devices. For BIPV envelopes to play these multi-functional roles in different applications, numerous factors should be considered. The design of BIPV envelopes involves a large set of envelope-related parameters, PV-related parameters, and conflicting performance criteria. Therefore, BIPV envelope design has become a complex process. Multi-objective optimization, which can optimize multiple objectives simultaneously, is an impressive way to support BIPV façade design and is rarely used in early building design.

Although there have been a small number of BIPV envelope design optimization studies, there is a mismatch between design practice and optimization models in terms of product and application types. Most current BIPV envelope design optimization frameworks are single objective which optimizes energy, cost, or carbon emissions. Further, existing multi-objective BIPV design optimization frameworks lack BIPV product and application type-related variables, and most studies cannot handle large sets of design variables and automatically generate a set of alternative optimal designs. Consideration of building envelope-related parameters and BIPV product-related parameters simultaneously in a MOO model has not been fully realized to date due to the complexity of the parameterization of variables. In addition, most BIPV optimization studies lack optimization algorithms which can handle a large set of design variables and constraints. At present, simulation tools integrated with optimization algorithms have become a common practice in the planning stages of the construction industry.
Therefore, the present research aims to develop a multi-objective optimization (MOO) framework to maximize life cycle energy (LCE) generation and minimize life cycle cost (LCC) considering multiple BIPV products, different BIPV application types and a set of building envelope features as design variables to support BIPV envelope design at the conceptual stage.
To achieve the research aim, this study includes four main objectives: 1. To explore the components of a building envelope design optimization framework that would be developed for the conceptual building design phase. 2. To establish an optimization process for different BIPV application types. 3.  To investigate the optimization algorithms and methods that could be used to optimize building envelope design for BIPV. 4. To develop and validate an optimization framework to integrate BIPV into the building structure. 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.

As the initial step, parameters related to BIPV envelope design optimization under the three major components of an optimization model: variables, constraints, and objective functions were identified. 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. LCE and LCC are the most widely used performance criteria for a BIPV system design and therefore, the study utilized those two objectives for the optimization process. The payback period is a major constraint in BIPV system design, and the building professionals always prefer positive net present value (NPV) in their designs. Therefore, payback and NPV constraints were incorporated as constraints in this framework. The interview findings from different building and BIPV related stakeholders further confirmed the above components for the BIPV envelope design optimization. 
The key part of the optimization framework is its optimization algorithm. Building envelope design optimization often involves more than one assessment criteria and hence, non-dominated-and-crowding Sorting Genetic Algorithm II (NSGA II) which is an evolutionary-based MOO algorithm, is selected for the study.  The proposed framework consists of two major process engines namely, the simulator and the optimizer. The simulator calculates the objective function values and the constraint values such as life cycle cost, life cycle energy, NPV and payback period while the optimizer engine optimizes the given building envelope for the selected BIPV application type considering multiple objectives, minimizing LCC and maximizing LCE.

Eleven case studies for different application types were optimized using the proposed framework and the results incorporate different design solutions for each application type. Furthermore, the results obtained revealed that the proposed optimization framework provides a much broader perspective on the design and optimization of BIPV systems considering multiple decision variables and constraints for different application areas. Therefore, building professionals can employ the proposed optimization framework as a viable option to support conceptual stage design decisions and to guide mid-design stage decisions related to BIPV.