An optimization framework for building energy retrofits decision-making

摘要

Buildings are major consumers of energy in the United States. One way to improve building's energy efficiency is through energy retrofitting. The selection of a combination of retrofitting measures for a specific building is a complex process. Despite of the numerous resources that provide advice on how to retrofit a facility, the study of important variables affecting this decision remains limited. Further research is needed on the development of decision-making models to select the optimum energy retrofitting strategy in order to maximize energy retrofitting benefits. This study proposes a decision making framework that: (1) calculates the economic benefits of energy retrofitting in terms of reduction of life-cycle cost for a specific building during its service life; (2) determines the optimum retrofitting budget that minimizes the total life-cycle cost of the building during its service-life; and (3) selects the optimum energy retrofitting strategy (among available energy retrofitting measures) to maximize the homeowner economic benefits during service-life of the building based on available investments. This study contributes to the body of knowledge in three aspects: (1) considering a comprehensive economic objective for decision-making in energy retrofits that includes majority of cost-related components of building life-cycle cost; (2) introducing a novel simplified energy prediction method by integrating dynamic and static modeling; and (3) incorporating energy retrofitting decision-making uncertainties to reach more accurate results. In order to demonstrate the implementation of the framework, a case study exercise of a house built in 1960's in Albuquerque, New Mexico is used. (C) 2017 Elsevier Ltd. All rights reserved.