Civil Engineering ETDs

Publication Date

Summer 7-28-2018


Buildings are major consumers of energy worldwide. On the other hand, over 60% of the US housing inventory is over 30 years old and a large number of these homes are energy inefficient. Therefore, it is essential to target the existing building stock for energy efficient interventions as a key to substantially reduce the adverse impacts of buildings on the environment and economy.

Building energy retrofitting has emerged as a primary strategy for reducing energy use and carbon emissions in existing buildings. An energy retrofit can be defined as a physical or operational change in a building, its energy-consuming equipment, or its occupants' energy-use behavior to convert the building to a lower energy consuming facility. Energy retrofitting could result in additional sustainable benefits such as reducing maintenance costs, reducing air emissions, creating job opportunities, enhancing human health, and improving thermal comfort among others.

One of the main challenges in building energy retrofitting is that several combinations of applicable energy consumption reducing measures can be considered to retrofit a building and it is a difficult task to choose the best retrofit strategy. Although numerous resources provide advice on how to retrofit a building, decisions regarding the optimal combination of retrofitting measures for a specific building are typically complex. In addition, most of the decisions for energy retrofits are based on limited cost categories rather than environmental and social considerations.

The main goal of this study is to develop a decision support system that integrates sustainable criteria (i.e. economic, environmental, and social benefits) in decision-making in energy retrofits. This goal will achieved through following objectives: (1) Determining the impact of building life-cycle on energy retrofitting decision-making; (2) Identifying and quantifying the sustainable benefits of building energy retrofitting to be used as an objective function in optimization problems; (3) Developing a systematic approach to select among different sustainable decision criteria for energy retrofitting decision-making; and (4) Developing and demonstrating a decision-making optimization model to select the best energy retrofitting alternative for a specific building while maximizing its sustainable benefits.

First a life-cycle cost analysis of the case study is presented in terms of energy retrofitting. This life-cycle cost analysis is used to explore the process of decision-making in energy retrofits. Then, a comprehensive study on identifying and quantifying the sustainable benefits of energy retrofits is performed that can be used in decision-making. Different tools such as literature review, surveys, Delphi technique, concept mapping approach, hedonic price modeling, and statistical analysis are used in this step. After that, a Sustainable Energy Retrofit (SER) decision support system is proposed. Finally, the application of this decision support system on a case study of a house located in Albuquerque, New Mexico is explored.

This research contributes to the body of knowledge by: (1) Integrating sustainable impacts of building energy retrofits (i.e. Economic, Environmental, and social) in decision-making; (2) Proposing a decision matrix that guides decision-makers on how to select the objective function(s) to formulate an optimization problem that results in the selection of the best energy retrofitting strategy, considering the benefits to investors; (3) Introducing a novel simplified energy prediction method by integrating dynamic and static modeling; (4) Measuring the implicit price of energy performance improvements in the US residential housing market; (5) Identifying, categorizing, and mapping the social sustainability criteria of energy improvements in existing buildings; and last but not least (6) Developing a decision-support system for energy retrofitting projects that integrates the above approaches.

The energy retrofitting decision-making model developed in this research can be implemented for different types of buildings to help decision-makers select the optimum energy retrofit strategy that not only maximizes monetary benefits, but also maximize environmental and social benefits. The presented research can also help homeowners to plan or evaluate their retrofitting strategies.


Energy-Retrofits; Decision-Making; Sustainability; LCCA

Document Type




Degree Name

Civil Engineering

Level of Degree


Department Name

Civil Engineering

First Committee Member (Chair)

Vanessa Valentin

Second Committee Member

Susan Bogus

Third Committee Member

Robert Berrens

Fourth Committee Member

Mark Russell