A multi-criterion decision analysis framework for sustainable energy retrofit in buildings. (15th January 2022) - Ongpeng, Jason Maximino C.; Rabe, Brian Immanuel B.; Razon, Luis F.; Aviso, Kathleen B.; Tan, Raymond R.
Abstract: Old buildings are known to have poor energy performance and have limited improvement options as they approach their end-of-life. The demand for sustainable design and construction of new buildings and the desire to improve the performance of existing ones is rapidly increasing. Given numerous retrofit options available, it is imperative to determine which criteria should be used to arrive at a logical and impartial choice. Multifarious and conflicting factors such as environmental, economic, social, and technical performance further complicate the decision-making process. To address this, a systematic hybrid decision framework is developed to evaluate energy retrofit strategies and to identify a compromise retrofit scenario which considers all stakeholders involved. The Analytic Hierarchy Process (AHP) is used to determine the relative weight of each criterion based on stakeholders' judgement while VIKOR is used to arrive at a compromise retrofit solution using relevant performance metrics. Although a Net-Zero Energy (NZE) scenario was proven technically feasible, this scenario was not identified as a compromise solution. Instead, three retrofit scenarios - on-site generation with high energy potential, mechanical/electrical with moderate energy potential, and building envelope with low energy potential showed good compromise for stakeholders. The proposed framework can be used as a tool by decision makers to arrive at compromise solutions that can benefit stakeholders. Highlights: Energy retrofitting of aged buildings needs to consider multiple conflicting factors. A hybrid decision model is developed to systematically select retrofit scenarios. A case study is conducted and showed that net-zero energy scenario is feasible and the least desired solution. The integrated framework provides more reliable decision support.